JUDEA PEARL – COGNITIVE SYSTEMS LABORATORY

Research was partially supported by grants from AFOSR, NIH, NSF and ONR (MURI).

(R-493):  [pdf] [bib]C. Cinelli, A. Forney, and J. Pearl “A Crash Course in Good and Bad Controls,”
UCLA Cognitive Systems Laboratory, Technical Report (R-493), March 2020.(R-492):  [pdf] [bib]C. Cinelli and J. Pearl “Generalizing Experimental Results by Leveraging Knowledge of Mechanisms,”
UCLA Cognitive Systems Laboratory, Technical Report (R-492), December 2019.(R-491-L):  [pdf] [bib]C. Zhang, B. Chen, and J. Pearl “A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models,”
UCLA Cognitive Systems Laboratory, Technical Report (R-491-L), December 2019.
Extended version of paper accepted to the Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI-2020).(R-489):  [pdf] [bib]J. Pearl “The Limitations of Opaque Learning Machines,”
UCLA Cognitive Systems Laboratory, Technical Report (R-489), May 2019.
Chapter 2 in John Brockman (Ed.), Possible Minds: 25 Ways of Looking at AI, Penguin Press, 2019.(R-488):  [pdf] [bib]A. Li and J. Pearl “Unit Selection Based on Counterfactual Logic,”
UCLA Cognitive Systems Laboratory, Technical Report (R-488), June 2019.
In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 1793-1799, 2019.(R-487):  [pdf] [bib]J. Pearl and Co-authored by D. Mackenzie, “Telling and re-telling history: The case for a whiggish account of the history of causation,”
UCLA Cognitive Systems Laboratory, Technical Report (R-487), March 2019.
(R-486):  [pdf] [bib]J. Pearl, “On the interpretation of do(x),”
UCLA Cognitive Systems Laboratory, Technical Report (R-486), February 2019.
Journal of Causal Inference, Causal, Casual, and Curious Section, 7(1), online, March 2019.(R-485):  [pdf] [bib]J. Pearl, “Causal and counterfactual inference,”
UCLA Cognitive Systems Laboratory, Technical Report (R-485), October 2019.
Forthcoming section in The Handbook of Rationality, MIT Press.(R-484):  [pdf] [bib]J. Pearl, “Sufficient Causes: On Oxygen, Matches, and Fires,”
UCLA Cognitive Systems Laboratory, Technical Report (R-484), September 2019.
Journal of Causal Inference, Causal, Casual, and Curious Section, AOP, https://doi.org/10.1515/jci-2019-0026, September 2019.(R-483):  [pdf] [bib]J. Pearl, “Does Obesity Shorten Life? Or is it the Soda? On Non-manipulable Causes,”
UCLA Cognitive Systems Laboratory, Technical Report (R-483), August 2018.
Journal of Causal Inference, Causal, Casual, and Curious Section, 6(2), online, September 2018.(R-482):  [pdf] [bib]C. Cinelli, D. Kumor, B. Chen, J. Pearl, and E. Bareinboim
“Sensitivity Analysis of Linear Structural Causal Models,”
UCLA Cognitive Systems Laboratory, Technical Report (R-482), June 2019.
Proceedings of the 36th International Conference on Machine Learning, PMLR 97, 1252-1261, 2019.(R-481):  [pdf] [bib]J. Pearl, “The Seven Tools of Causal Inference with Reflections on Machine Learning,”
UCLA Cognitive Systems Laboratory, Technical Report (R-481), July 2018.
Communications of ACM, 62(3): 54-60, March 2019(R-480):  [pdf] [bib]Karthika Mohan, Felix Thoemmes, Judea Pearl, “Estimation with Incomplete Data: The Linear Case,”
UCLA Cognitive Systems Laboratory, Technical Report (R-480), May 2018.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), 5082-5088, 2018.(R-479):  [pdf] [bib]C. Cinelli and J. Pearl, “RE: A Practical Example Demonstrating the Utility of Single-world Intervention Graphs,”
UCLA Cognitive Systems Laboratory, Technical Report (R-479), April 2018.
Journal of Epidemiology, 29(6): e50–e51, November 2018.(R-478):  [pdf] [bib]J. Pearl and E. Bareinboim, “A note on `Generalizability of Study Results’,”
UCLA Cognitive Systems Laboratory, Technical Report (R-478), April 2018.
Epidemiology, 30(2):186–188, March 2019.(R-477):  [pdf] [bib]J. Pearl, “Challenging the Hegemony of Randomized Controlled Trials: Comments on Deaton and Cartwright,”
UCLA Cognitive Systems Laboratory, Technical Report (R-477), April 2018.
Social Science and Medicine, published online, April 2018.(R-477):  [pdf] [bib]J. Pearl, “A Personal Journey into Bayesian Networks,”
UCLA Cognitive Systems Laboratory, Technical Report (R-476), May 2018.
(R-475):  [pdf] [bib]J. Pearl, “Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution”
UCLA Cognitive Systems Laboratory, Technical Report (R-475), July 2018.
Paper supporting Keynote Talk at WSDM’18: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. 3. 2018.
(R-474):  [pdf] [bib]J. Pearl, “Comments on `The Tale Wagged by the DAG'”
UCLA Cognitive Systems Laboratory, Technical Report (R-474), January 2018.
International Journal of Epidemiology, 47(3):1002-1004, 2018.(R-473):  [pdf] [bib]K. Mohan and J. Pearl, “Graphical Models for Processing Missing Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-473-L), June 2019.
Forthcoming, Journal of American Statistical Association (JASA).(R-472):  [pdf] [bib]J. Pearl, “What is Gained from Past Learning”
UCLA Cognitive Systems Laboratory, Technical Report (R-472), March 2018.
Journal of Causal Inference, Causal, Casual, and Curious Section, 6(1), Article 20180005, March 2018. https://doi.org/10.1515/jci-2018-0005(R-471):  [pdf] [bib]A. Forney, J. Pearl, and E. Bareinboim, “Counterfactual Data-Fusion for Online Reinforcement Learners”
UCLA Cognitive Systems Laboratory, Technical Report (R-471), June 2017.
Presented at the Transfer in Reinforcement Learning workshop at AAMAS-2017.
Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1156-1164, 2017.(R-470):  [pdf] [bib]J. Pearl, “The Eight Pillars of Causal Wisdom”
UCLA Cognitive Systems Laboratory, Technical Report (R-470), April 2017.
(R-469): J. Pearl, “A Personal Journey into Bayesian Networks,”
UCLA Cognitive Systems Laboratory, Technical Report (R-476), May 2018.
(R-466):  [pdf] [bib]J. Pearl “The Sure-Thing Principle”
UCLA Cognitive Systems Laboratory, Technical Report (R-466), February 2016.
Journal of Causal Inference, Causal, Casual, and Curious Section, 4(1):81-86, March 2016.(R-461):  [pdf] [bib]B. Chen, J. Pearl, and E. Bareinboim, “Incorporating Knowledge into Structural Equation Models using Auxiliary Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-461), July 2016.
In S. Kambhampati (Ed.), Proceedings of the 25 International Joint Conference on Artificial Intelligence (IJCAI), Palo Alto: AAAI Press, 3577-3583, 2016.
(R-461-L):  [pdf]B. Chen, J. Pearl, and E. Bareinboim, “Incorporating Knowledge into Structural Equation Models using Auxiliary Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-461-L), April 2016.
Extended version of paper in S. Kambhampati (Ed.), Proceedings of the 25 International Joint Conference on Artificial Intelligence (IJCAI), Palo Alto: AAAI Press, 3577-3583, 2016.(R-460):  [pdf] [bib]E. Bareinboim, Andrew Forney, and J. Pearl, “Bandits with Unobserved Confounders: A Causal Approach”
UCLA Cognitive Systems Laboratory, Technical Report (R-460), November 2015.
In C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama, and R. Garnett (Eds.), Neural Information Processing Systems (NIPS) Conference, Advances in Neural Information Processing Systems 28, Curran Associates, Inc., pp. 1342-1350, 2015.(R-459):  [pdf] [bib]J. Pearl, “A Linear `Microscope’ for Interventions and Counterfactuals”
UCLA Cognitive Systems Laboratory, Technical Report (R-459), March 2017.
Journal of Causal Inference, Causal, Casual, and Curious Section, published online 5(1):1-15, March 2017.(R-457):  [pdf] [bib]J. Pearl, “Indirect Confounding and Causal Calculus (On three papers by Cox and Wermuth)”
UCLA Cognitive Systems Laboratory, Technical Report (R-457), July 2015.
(R-456):  [pdf] [bib]J. Pearl, “Causal Thinking in the Twilight Zone”
UCLA Cognitive Systems Laboratory, Technical Report (R-456), July 2015.
Observational Studies, Special Issue on William Cochran’s contributions, Vol. 1, pp. 200-204, 2015.
(R-454):  [pdf] [bib]I. Shpitser, K. Mohan, and J. Pearl, “Missing data as a causal and probabilistic problem”
UCLA Cognitive Systems Laboratory, Technical Report (R-454), July 2015.
In Marina Meila and Tom Heskes (Eds.), Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, Corvallis, OR: AUAI Press, 802–811, 2015.
(R-452):  [pdf] [bib]J. Pearl, “Generalizing experimental findings”
UCLA Cognitive Systems Laboratory, Technical Report (R-452), July 2015.
Journal of Causal Inference, Causal, Casual, and Curious Section, 3(2):259-266, September 2015.(R-451):  [pdf] [bib]A. Hannart, J. Pearl, F.E.L. Otto, P. Naveau and M. Ghil, “Causal counterfactual theory for the attribution of weather and climate-related events”
UCLA Cognitive Systems Laboratory, Technical Report (R-451), March 2015.
Bulletin of the American Meteorological Society, 97(1):99-110, 2016.(R-450):  [pdf] [bib]E. Bareinboim and J. Pearl, “Causal inference and the data-fusion problem”
UCLA Cognitive Systems Laboratory, Technical Report (R-450), July 2016.
Proceedings of the National Academy of Sciences, 113(27): 7345-7352, 2016.
(R-449):  [pdf] [bib]B. Chen and J. Pearl “Exogeneity and Robustness”
UCLA Cognitive Systems Laboratory, Technical Report (R-449), November 2015.
(R-448):  [pdf] [bib]F. Thoemmes and K. Mohan “Graphical Representation of Missing Data Problems”
UCLA Cognitive Systems Laboratory, Technical Report (R-448), January 2015.
Structural Equation Modeling: A Multidisciplinary Journal, 22(2):631-642, 2015.(R-447):  [pdf] [bib]J. Pearl “Conditioning on Post-Treatment Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-447), February 2015.
Journal of Causal Inference, Causal, Casual, and Curious Section, 3(1): 131-137, March 2015. Includes Appendix (appended to published version).(R-446):  [pdf] [bib]J. Pearl “Comment on Ding and Miratrix: `To Adjust or Not to Adjust?'”
UCLA Cognitive Systems Laboratory, Technical Report (R-446), January 2015.
Journal of Causal Inference, 3(1): 59-60, 2015.(R-445):  [pdf] [bib]E. Bareinboim and J. Tian “Recovering Causal Effects from Selection Bias”
UCLA Cognitive Systems Laboratory, Technical Report (R-445), December 2014.
In Sven Koenig and Blai Bonet (Eds.), Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, pp. 3475-3481, 2015.(R-444):  [pdf] [bib]B. Chen, “Identification and Overidentification of Linear Structural Equation Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-444), February 2017.
In D.D. Lee, M. Sugiyama, U.V. Luxburg, I. Guyon, and R. Garnett (Eds.), Advances in Neural Information Processing Systems 29, Curran Associates, Inc., pp. 1579-1587, 2016.
(R-444-Appendix):  [pdf](R-443):  [pdf] [bib]E. Bareinboim and J. Pearl “Transportability from Multiple Environments with Limited Experiments: Completeness Results”
UCLA Cognitive Systems Laboratory, Technical Report (R-443), November 2014.
In In Z. Ghahramani and M. Welling and C. Cortes and N.D. Lawrence and K.Q. Weinberger (eds.), Advances of Neural Information Processing Systems 27 (NIPS 2014) , 280-288, 2014.(R-442):  [pdf] [bib]K. Mohan and J. Pearl “Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-442), November 2014.
In M. Welling, Z. Ghahramani, C. Cortes, and N. Lawrence (eds.), Advances of Neural Information Processing 27 (NIPS Proceedings), 1520-1528, 2014.(R-441):  [pdf] [bib]G. Van den Broeck, K. Mohan, A. Choi, and J. Pearl “Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-441), November 2014.
Presented at the Causal Modeling and Machine Learning Workshop at ICML-2014.
(R-441-UAI):  [pdf] [bib]G. Van den Broeck, K. Mohan, A. Choi, A. Darwiche, and J. Pearl “Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-441-UAI), July 2015.
Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence, pp. 161-170, 2015.
(R-441-Supplemental):  [Supplemental](R-439):  [pdf] [bib]J. Pearl “A Note on Causes of Effects”
UCLA Cognitive Systems Laboratory, Technical Report (R-439), September 2014.
(R-437):  [pdf] [bib]J. Pearl “In Defense of Unification (Comments on West and Koch’s review of Causality)”
UCLA Cognitive Systems Laboratory, Technical Report (R-437), September 2014.
(R-436):  [pdf-aop] [bib]J. Pearl “Lord’s Paradox Revisited — (Oh Lord! Kumbaya!)”
UCLA Cognitive Systems Laboratory, Technical Report (R-436), October 2016.
Journal of Causal Inference, Causal, Casual, and Curious Section, 4(2), September 2016.(R-433):  [pdf] [bib]J. Pearl “A Short Note on the Virtues of Graphical Tools”
UCLA Cognitive Systems Laboratory, Technical Report (R-433), July 2014.
(R-432):  [pdf] [bib]B. Chen and J. Pearl “Graphical Tools for Linear Structural Equation Modeling”
UCLA Cognitive Systems Laboratory, Technical Report (R-432), July 2015.
(R-431):  [pdf] [bib]J. Pearl “Causes of Effects and Effects of Causes”
UCLA Cognitive Systems Laboratory, Technical Report (R-431), February 2015.
Journal of Sociological Methods and Research, 44(1): 149-164, 2015.
(R-431-L):  [pdf] [bib]J. Pearl “Causes of Effects and Effects of Causes”
UCLA Cognitive Systems Laboratory, Technical Report (R-431-L), October 2014.
Long version of paper in Journal of Sociological Methods and Research, 44(1): 149-164, 2015.(R-430):  [pdf] [bib]E. Y.-J. Chen and J. Pearl “Random Bayesian networks with bounded indegree”
UCLA Cognitive Systems Laboratory, Technical Report (R-430), April 2014.
In Proceedings of the 17th International Conference on Articial Intelligence and Statistics (AISTATS) 2014, Reykjavik, Iceland. JMLR: W&CP volume 33.(R-428):  [pdf] [bib]B. Chen, J. Tian, and J. Pearl “Testable Implications of Linear Structural Equations Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-428), May 2014.
In Carla E. Brodley and Peter Stone (Eds.),Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, 2424–2430, 2014.(R-425):  [pdf] [bib]E. Bareinboim, J. Tian, and J. Pearl “Recovering from Selection Bias in Causal and Statistical Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-425), July 2014.
In Carla E. Brodley and Peter Stone (Eds.) Proceedings of the Twenty-eighth AAAI Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, 2410-2416, 2014, “Best Paper Award.”(R-424):  [pdf] [bib]J. Pearl “The Deductive Approach to Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-424), June 2014.
Journal of Causal Inference Volume 2, Issue 2, 115-129, September 2014. (DOI: doi 10.1515/jci-2014-0016)(R-422):  [pdf] [bib]J. Pearl “Is Scientific Knowledge Useful for Policy Analysis? A Peculiar Theorem says: No”
UCLA Cognitive Systems Laboratory, Technical Report (R-422), March 2014.
Journal of Causal Inference, Causal, Casual, and Curious Section, 2(1): 109–112, March 2014.(R-421):  [pdf] [bib]J. Pearl “Reply to Commentary by Imai, Keele, Tingley, and Yamamoto Concerning Causal Mediation Analysis”
UCLA Cognitive Systems Laboratory, Technical Report (R-421), June 2014.
Psychological Methods, Vol. 19, No. 4, 488-492, 2014. Click here for original article (R-389) with Comment and Reply(R-420):  [pdf] [bib]J. Pearl “Reflections on Heckman and Pinto’s `Causal Analysis After Haavelmo,'”
UCLA Cognitive Systems Laboratory, Technical Report (R-420), November 2013.
Working paper.(R-419):  [pdf] [bib]E. Bareinboim, S. Lee, V. Honavar, and J. Pearl “Causal Transportability from Multiple Environments with Limited Experiments,”
UCLA Cognitive Systems Laboratory, Technical Report (R-419), December 2013.
In C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger (Eds.), Advances of Neural Information Processing 26 (NIPS Proceedings), 136–144, 2013.(R-417):  [pdf] [bib]J. Pearl and K. Mohan “Recoverability and testability of missing data: Introduction and summary of results,”
UCLA Cognitive Systems Laboratory, Technical Report (R-417), January 2014.
(Based on slides presented by J. Pearl on August 6, 2013, at JSM-13, Montreal, CA)(R-416):  [pdf] [bib]  J. Pearl “The Mathematics of Causal Inference,”
UCLA Cognitive Systems Laboratory, Technical Report (R-416), September 2013.
IMS 2013 Medallion Lecture VI.
In Proceedings of the Joint Statistical Meetings Conference, Section on Statistical Education, Alexandria, VA: American Statistical Association, 2515-2529, 2013.(R-415):  [pdf] [bib]K. Mohan and J. Pearl “On the Testability of Models with Missing Data,”
UCLA Cognitive Systems Laboratory, Technical Report (R-415), April 2014.
In Samuel Kaski and Jukka Corander (Eds.) JMLR Workshop and Conference Proceedings Volume 33: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 643-650, 2014.(R-414):  [pdf] [bib]  J. Pearl “Understanding Simpson’s Paradox,”
UCLA Cognitive Systems Laboratory, Technical Report (R-414), December 2013.
The American Statistician, Vol. 68(1): 8–13, 2014. With discussions [1], [2], [3], [4], [5](R-413): [pdf] [bib]  J. Pearl “Structural counterfactuals: A brief introduction,”
UCLA Cognitive Systems Laboratory, Technical Report (R-413), June 2013.
Cognitive Science, 37, pp. 977-985, 2013.(R-412):  [pdf] [bib]  J. Pearl “Comment on `Causal inference, probability theory, and graphical insights’ (by Stuart G. Baker),”
UCLA Cognitive Systems Laboratory, Technical Report (R-412), June 2013.
Statistics in Medicine, 32(25): 4331-4333, November 2013.(R-411):  [pdf] [bib]  J. Pearl “Comments on `Surrogate measures and consistent surrogates’ (by Tyler VanderWeele),”
UCLA Cognitive Systems Laboratory, Technical Report (R-411), March 2013.
Biometrics, 69(3): 575-577, September 2013.(R-410):  [pdf] [bib]  K. Mohan, J. Pearl, and J. Tian “Graphical Models for Inference with Missing Data,”
UCLA Cognitive Systems Laboratory, Technical Report (R-410), November 2013.
In C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger (Eds.), Advances in Neural Information Processing System 26 (NIPS-2013), 1277–1285, 2013.(R-409):  [pdf] [bib]  J. Pearl “Linear Models: A Useful “Microscope” for Causal Analysis”
UCLA Cognitive Systems Laboratory, Technical Report (R-409), March 2013.
Journal of Causal Inference, Causal, Casual, and Curious Section, 1(1):155–170, May 2013. (DOI: 10.1515/jci-2013-0003)(R-408):  [pdf] [bib]  E. Bareinboim and J. Pearl “Causal Transportability with Limited Experiments”
UCLA Cognitive Systems Laboratory, Technical Report (R-408), April 2013.
In Proceedings of the 27th AAAI Conference on Artificial Intelligence, pp. 95–101, 2013.(R-407):  [pdf] [bib]  E. Bareinboim and J. Pearl “Meta-Transportability of Causal Effects: A Formal Approach”
UCLA Cognitive Systems Laboratory, Technical Report (R-407), February 2013.
In Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 135–143, 2013.(R-406):  [pdf] [bib]  J. Pearl “Detecting Latent Heterogeneity”
UCLA Cognitive Systems Laboratory, Technical Report (R-406), First version: December 2012, Revised verssion: July 2015.
Sociological Methods and Research, DOI: 10.1177/0049124115600597, online pp. 1-20, 2015. (Appendices added to end of reprint.)(R-405):  [pdf] [bib]  J. Pearl “A solution to a class of selection-bias problems”
UCLA Cognitive Systems Laboratory, Technical Report (R-405), December 2012.
(R-404):  [pdf] [bib]  E. Bareinboim and J. Pearl “A General Algorithm for Deciding Transportability of Experimental Results,”
UCLA Cognitive Systems Laboratory, Technical Report (R-404), March 2013.
Journal of Causal Inference, Volume 1, Issue 1, pp 107-134, May 2013. (DOI: 10.1515/jci-2012-0004)(R-402):  [pdf] [bib]  J. Pearl “Do-Calculus Revisited”
UCLA Cognitive Systems Laboratory, Technical Report (R-402), August 2012.
In Nando de Freitas and Kevin Murphy (Eds.), Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Corvallis, OR: AUAI Press, 4-11, 2012.(R-400):  [pdf] [bib]  J. Pearl and E. Bareinboim “External validity: From do-calculus to transportability across populations”
UCLA Cognitive Systems Laboratory, Technical Report (R-400), First version: May 2012: Last revision: May 2014.
Statistical Science, 29(4): 579-595, 2014.(R-399):  [pdf] [bib]  J. Pearl “Book Reviews: Bias and Causation, Models and Judgment for Valid Comparisions by H.I. Weisberg”
UCLA Cognitive Systems Laboratory, Technical Report (R-399), March 2012.
Biometrics, Volume 68(2):659–660, 2012.(R-397):  [pdf] [bib]  E. Bareinboim and J. Pearl “Causal Inference by Surrogate Experiments: z-Identifiability”
UCLA Cognitive Systems Laboratory, Technical Report (R-397), June 2012.
In Nando de Freitas and Kevin Murphy (Eds.), Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Corvallis, OR: AUAI Press, 113-120. 2012.(R-396):  [pdf] [bib]  J. Pearl “Graphoids over counterfactuals”
UCLA Cognitive Systems Laboratory, Technical Report (R-396), January 2013.
Journal of Causal Inference, Causal, Casual, and Curious Section, 2(2):243-248, September 2014 (DOI: 10.1515/jci-2014-0028).(R-395):  [pdf] [bib]  B. Chen and J. Pearl “Regression and Causation: A Critical Examination of Six Econometrics Textbooks”
UCLA Cognitive Systems Laboratory, Technical Report (R-395), September 2013.
Real-World Economics Review, Issue No. 65, 2–20, 2013.
For extended survey by Chris Auld, click here(R-394):  [pdf] [bib]  J. Pearl “Correlation and Causation — the logic of co-habitation”
UCLA Cognitive Systems Laboratory, Technical Report (R-394), June 2012.
European Journal of Personality, Special Issue, Vol. 26, 401-402, 2012.(R-393):  [pdf] [bib]  K.A. Bollen and J. Pearl “Eight Myths about Causality and Structural Equation Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-393), July 2012.
In S.L. Morgan (Ed.) Handbook of Causal Analysis for Social Research, Chapter 15, 301-328, Springer, 2013.(R-392):  [pdf] [bib]  J. Pearl “A note on the pairwise Markov condition in directed Markov fields”
UCLA Cognitive Systems Laboratory, Technical Report (R-392), April 2012.
(R-391):  [pdf] [bib]  J. Pearl “Trygve Haavelmo and the Emergence of Causal Calculus”
UCLA Cognitive Systems Laboratory, Technical Report (R-391), 1st version, February 2012; 2nd Revision, August 2012; 3rd Revision, September 2012; 4th Revision, February 2013; 5th Revision, January 2014.
Econometric Theory, Special Issue on Haavelmo Centennial, 31(1) 152-179, February 2015. (Published online: 10 June 2014. DOI: http://dx.doi.org/10.1017/S0266466614000231.)(R-390-L):  [pdf] [bib]  E. Bareinboim and J. Pearl “Transportability of Causal Effects: Completeness Results”
UCLA Cognitive Systems Laboratory, Technical Report (R-390), April 2012.
Extended version of paper in Proceedings of the 26th AAAI Conference, Toronto, Ontario, Canada, pp. 698-704, 2012.(R-389):  [pdf] [bib]  J. Pearl “Interpretation and Identification of Causal Mediation”
UCLA Cognitive Systems Laboratory, Technical Report (R-389), June 2014.
Psychological Methods, Vol. 19, No. 4, 459-481, 2014. Click here for complete article with Comment and Reply(R-387):  [pdf] [bib]  J. Pearl “Some Thoughts Concerning Transfer Learning, with Applications to Meta-analysis and Data-sharing Estimation”
UCLA Cognitive Systems Laboratory, Technical Report (R-387), January 2012.
Working paper.(R-386):  [pdf] [AJE] [bib]  J. Pearl “Invited Commentary: Understanding Bias Amplification”
UCLA Cognitive Systems Laboratory, Technical Report (R-386), October 2011.
Advance access, American Journal of Epidemiology, 174(11):1223-1227. DOI: 10.1093/aje/kwr352.(R-384):  [pdf] [bib]  E. Bareinboim, C. Brito, and J. Pearl “Local Characterizations of Causal Bayesian Networks”
UCLA Cognitive Systems Laboratory, Technical Report (R-384), May 2011.
In M. Croitoru, S. Rudolph, N. Wilson, J. Howse, and O. Corby (Eds.),
GKR 2011, LNAI 7205, Berlin Heidelberg: Springer-Verlag, pp. 1-17, 2012.(R-382):  [pdf] [bib]  J. Pearl “Principal Stratification – A goal or a tool?”
UCLA Cognitive Systems Laboratory, Technical Report (R-382), March 2011.
The International Journal of Biostatistics Vol. 7: Issue 1, Article 20, Pages 1-13, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1322, March 2011.
(R-381):  [pdf] [bib]  E. Bareinboim and J. Pearl “Controlling Selection Bias in Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-381), February 2012.
In Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS), La Palma, Canary Islands, April 21-23, pp. 100-108, 2012.(R-380):  [pdf] [bib]  J. Pearl “Comments and Controversies: Graphical models, potential outcomes and causal inference: Comment on Lindquist and Sobel”
UCLA Cognitive Systems Laboratory, Technical Report (R-380), August 2011.
NeuroImage Vol. 58, pp. 770-771, 2011.
http://www.sciencedirect.com/science/article/pii/S105381191100615X; DOI information: 10.1016/j.neuroimage.2011.06.007(R-379):  [pdf] [bib]  J. Pearl “The Causal Mediation Formula — A Guide to the Assessment of Pathways and Mechanisms”
UCLA Cognitive Systems Laboratory, Technical Report (R-379), October 2011.
Prevention Science, 13:426-436, DOI: 10.1007/s11121-011-0270-1, March 2012.(R-376):  [pdf] [bib]  J. Pearl “Foreword”
UCLA Cognitive Systems Laboratory, Technical Report (R-376), June 2011.
In Targeted Learning by Mark J. van der Laan and Sherri Rose, Springer, New York, pp. vii–x, 2011.(R-375):  [pdf] [bib]  J. Pearl “The Curse of Free-will and the Paradox of Inevitable Regret”
UCLA Cognitive Systems Laboratory, Technical Report (R-375), December 2013.
Journal of Causal Inference, Causal, Casual, and Curious Section, 1(2):255-257, December 2013.(R-373):  [pdf] [bib]  J. Pearl “Statistics and Causality: Separated to Reunite Commentary on Bryan Dowd’s `Separated at Birth'”
UCLA Cognitive Systems Laboratory, Technical Report (R-373), January 2011.
Health Services Research, 46(2):421-429, April 2011. DOI: 10.1111/j.1475-6773.2011.01243.x(R-372):  [pdf] [bib]  J. Pearl and E. Bareinboim “Transportability across studies: A formal approach”
UCLA Cognitive Systems Laboratory, Technical Report (R-372), Original version July 2011, Revised July 2018.
(R-372-A):  [pdf] [bib]  Short version, “Transportability of Causal and Statistical Relations: A Formal Approach”
In Proceedings of the 25th AAAI Conference on Artificial Intelligence, August 7-11, 2011, San Francisco, CA. AAAI Press, Menlo Park, CA, pp. 247-254.
(R-372-JSM):  [pdf] [bib]  “External Validity and Transportability: A Formal Approach”
2011 JSM Proceedings, Miami Beach FL, July 30-August 4, 2011, pp. 157-171.(R-370):  [pdf] [bib]  J. Pearl, “The Causal Foundations of Structural Equation Modeling”
UCLA Cognitive Systems Laboratory, Technical Report (R-370), March 2012.
Chapter for R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling. New York: Guilford Press, Chapter 5, pp. 68-91, 2012.(R-369):  [pdf] [bib]  S. Greenland and J. Pearl, “Adjustments and their Consequences — Collapsibility Analysis using Graphical Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-369), September 2011.
International Statistical Review, 79(3):401-426, 2011. doi:10.1111/j.1751-5823.2011.00158.x.(R-368):  [pdf] [bib]  Y. Weiss and J. Pearl, “Belief Propagation — Perspectives”
UCLA Cognitive Systems Laboratory, Technical Report (R-368), July 2010.
Communications of the ACM, Vol. 53(10): 1, October 2010.(R-366):  [pdf] [bib]  M. Kuroki and J. Pearl, “Measurement Bias and Effect Restoration in Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-366), October 2011.
Biometrika, 101(2), 423-437, 2014.(R-364):  [pdf] [bib]  T. Kyono, “Commentator: A Front-End User-Interface Module for Graphical and Structural Equation Modeling”
UCLA Cognitive Systems Laboratory, Technical Report (R-364), May 2010.
Master Thesis(R-363):  [pdf] [bib]  J. Pearl, “The Mediation Formula: A guide to the assessment of causal pathways in nonlinear models”
UCLA Cognitive Systems Laboratory, Technical Report (R-363), October 2011.
In C. Berzuini, P. Dawid, and L. Bernardinelli (Eds.), Causality: Statistical Perspectives and Applications John Wiley and Sons, Ltd, Chichester, UK, pp. 151-179, 2012.(R-361):  [pdf] [bib]  S. Greenland and J. Pearl, “Causal Diagrams”
UCLA Cognitive Systems Laboratory, Technical Report (R-361), November 2009.
Wiley StatsRef: Statistics Reference Online, © 2014-2017 John Wiley & Sons, Ltd. 1
This article is © 2017 John Wiley & Sons, Ltd. DOI: 10.1002/9781118445112.stat03732.pub2
Previous version in M. Lovric (Ed.), International Encyclopedia of Statistical Science 2011, Part 3, pp. 208-216, DOI: 10.1007/978-3-642-04898-2_162(R-360):  [SpringerLink]   [pdf] [bib]  J. Pearl, “The algorithmization of counterfactuals”
UCLA Cognitive Systems Laboratory, Technical Report (R-360), June 2011.
Annals for Mathematics and Artificial Intelligence, 61(1):29-39, DOI: 10.1007/s10472-011-9247-9, 2011.(R-359):  [pdf] [bib]  J. Pearl, “Physical and Metaphysical Counterfactuals”
UCLA Cognitive Systems Laboratory, Technical Report (R-359), January 2010.
Revised version, Journal of Causal Inference, Causal, Casual, and Curious Section, 5(2): September 2017.(R-358):  [pdf] [bib]  J. Pearl, “On the Consistency Rule in Causal Inference: An Axiom, Definition, Assumption, or a Theorem?”
UCLA Cognitive Systems Laboratory, Technical Report (R-358), February 2010.
Epidemiology, Vol. 21(6):872-875, 2010.(R-357):  [pdf] [bib]  J. Pearl, “On Measurement Bias in Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-357), June 2010.
In P. Grunwald and P. Spirtes, editors, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 425–432. AUAI, Corvallis, OR, 2010.(R-356):  [pdf] [bib]  J. Pearl, “On a Class of Bias-Amplifying Variables that Endanger Effect Estimates”
UCLA Cognitive Systems Laboratory, Technical Report (R-356), June 2010.
In P. Grunwald and P. Spirtes, editors, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 417–424. AUAI, Corvallis, OR, 2010.(R-355):  [pdf] [bib]  J. Pearl, “The Foundations of Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-355), August 2010.
Sociological Methodology, Vol. 40(1):75-149, 2010.(R-354):  [pdf] [bib]  J. Pearl, “An Introduction to Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-354), February 2010.
The International Journal of Biostatistics, Vol. 6 : Iss. 2, Article 7, 2010.
DOI: 10.2202/1557-4679.1203
(R-351):  [pdf] [bib]  J. Pearl, “The Structural Theory of Causation”
UCLA Cognitive Systems Laboratory, Technical Report (R-351), July 2009.
In P. McKay Illari, F. Russo, and J. Williamson (Eds.),
Causality in the Sciences, Chapter 33, Clarendon Press, Oxford, 697–727, 2011.
(R-350):  [pdf] [bib]  J. Pearl, “Causal inference in statistics: An overview”
UCLA Cognitive Systems Laboratory, Technical Report (R-350), September 2009.
Statistics Surveys, Vol. 3, 96–146, 2009.(R-349):  [pdf] [bib]I. Shpitser and J. Pearl, “Effects of Treatment on the Treated: Identification and Generalization”
In J. Bilmes and A. Ng (Eds.), Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, AUAI Press, 514–521, 2009.(R-349-L):  [pdf] [bib]I. Shpitser and J. Pearl, “Effects of Treatment on the Treated: Identification and Generalization”
UCLA Cognitive Systems Laboratory, Technical Report (R-349), August 2009.
Extended version of paper that appeared in UAI-09.(R-348):  [pdf] [bib]J. Pearl, “Myth, Confusion, and Science in Causal Analysis”
UCLA Cognitive Systems Laboratory, Technical Report (R-348), May 2009.
Warning: Contains controversial material – may spoil the youth. Seeking an enlightened editor who recognizes its merits.(R-347):  [pdf] [bib]J. Pearl, “The Science and Ethics of Causal Modeling”
UCLA Cognitive Systems Laboratory, Technical Report (R-347), February 2011.
In Handbook of Ethics in Quantitative Methodology, A.T. Panter and Sonya Serba (Eds.), New York: Taylor and Francis Group, 383–414, 2011.(R-346):  [pdf] [bib]J. Pearl, “Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-346), June 2009.
In Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings; Causality: Objectives and Assessment (NIPS 2008), Vol. 6: 39–58, 2010.(R-345):  [pdf] [bib]J. Pearl, “Letter to the Editor: Remarks on the Method of Propensity Score”
UCLA Cognitive Systems Laboratory, Technical Report (R-345), December 2008.
Statistics in Medicine, Vol. 28, 1420-1423, 2009.(R-343):  [pdf] [bib]J. Pearl and A. Paz, “Confounding Equivalence in Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-343), June 2010.
In P. Grunwald and P. Spirtes, editors, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 433–441. AUAI, Corvallis, OR, 2010.
(R-343w):  [pdf] [bib] Journal of Causal Inference 2(1):75–93, April 2014. (DOI: 10.1515/jci-2013-0020)(R-342):  [pdf] [bib]J. Pearl, “Review of N. Cartwright `Hunting Causes and Using Them'”
UCLA Cognitive Systems Laboratory, Technical Report (R-342), September 2008.
Economics and Philosophy, Vol. 26, 69-77, 2010.(R-341):  [pdf] [bib]I. Shpitser “Complete Identification Methods for Causal Inference”
UCLA Cognitive Systems Laboratory, Technical Report (R-341), April 2008.
Ph.D. Thesis(R-340):  [pdf] [bib]I. Shpitser and J. Pearl, “Dormant Independence”
UCLA Cognitive Systems Laboratory, Technical Report (R-340), April 2008.
In Proceedings of the Twenty-Third Conference on Artificial Intelligence, 1081-1087, 2008.
(R-340-L):  [pdf] [bib](R-338):  [pdf] [bib]J. Pearl, “The Mathematics of Causal Relations”
UCLA Cognitive Systems Laboratory, Technical Report (R-338), March 2008.
Presented at the American Psychopathological Association (APPA) Annual Meeting, NYC, March 6-8, 2008.
In P.E. Shrout, K. Keyes, and K. Ornstein (Eds.), Causality and Psychopathology: Finding the Determinants of Disorders and their Cures, Oxford University Press, 47-65, 2010.(R-337):  [pdf] [bib]J. Pearl, “The Mathematics of Causal Inference in Statistics”
UCLA Cognitive Systems Laboratory, Technical Report (R-337), October 2007.
In 2007 JSM Proceedings of the American Statistical Association, Biometrics Section [CD-ROM], Alexandria, VA: American Statistical Association: pp. 19-26.(R-336):  [pdf] [bib]I. Shpitser and J. Pearl, “Complete Identification Methods for the Causal Hierarchy”
UCLA Cognitive Systems Laboratory, Technical Report (R-336), February 2008.
Journal of Machine Learning Research, Vol. 9, pp. 1941-1979, 2008.(R-335):  [pdf] [bib]Z. Cai, M. Kuroki, J. Pearl, and J. Tian, “Bounds on Direct Effect in the Presence of Confounded Intermediate Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-335), September 2007.
Biometrics, Vol. 64, 695-701, 2008.(R-334):  [pdf] [bib]I. Shpitser and J. Pearl, “What Counterfactuals Can Be Tested”
UCLA Cognitive Systems Laboratory, Technical Report (R-334), May 2007.
In Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence, 352–359, 2007.(R-333):  [pdf]  C. Brito and J. Pearl, “Graphical Condition for Identification in Recursive SEM”
UCLA Cognitive Systems Laboratory, Technical Report (R-333), May 2006.
In R. Dechter and T.S. Richardson (Eds.), Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence, 47-54, Corvallis, OR: AUAI Press, 2006.(R-332):  [pdf]  S. Greenland, J. Pearl, “Causal Diagrams,”
UCLA Cognitive Systems Laboratory, Technical Report (R-332), June 2006.
In S. Boslaugh (Ed.), Encyclopedia of Epidemiology, Thousand Oaks, CA: Sage Publications, 149–156, 2007.(R-331):  [pdf]  J. Pearl, “Two journeys into human reasoning,”
UCLA Cognitive Systems Laboratory, Technical Report (R-331), June 2006.
To appear in Paul Cohen (Ed.) 50 years to AI.(R-329):  [pdf]  I. Shpitser, J. Pearl, “Identification of Conditional Interventional Distributions”
UCLA Cognitive Systems Laboratory, Technical Report (R-329), May 2006.
In R. Dechter and T.S. Richardson (Eds.), Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence, 437-444, Corvallis, OR: AUAI Press, 2006.
Awarded UAI-2006 Best Student Paper jointly with Yimin Huang and Marco Valtorta (University of South Carolina) for their paper “Pearl’s Calculus of Intervention is Complete”(R-329-APPENDUM):  [pdf]  I. Shpitser, “Appendum to Identification of Conditional Interventional Distributions”
UCLA Cognitive Systems Laboratory, Technical Report (R-329-APPENDUM), May 2007.(R-328):  [pdf]  J. Tian, C. Kang, and J. Pearl, “A Characterization of Interventional Distributions in Semi-Markovian Causal Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-328), June 2006.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence AAAI Press, Menlo Park, CA, 1239-1244, July 2006.(R-327):  [pdf]  I. Shpitser, J. Pearl, “Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-327), February 2006.
In Proceedings of the Twenty-First National Conference on Artificial Intelligence AAAI Press, Menlo Park, CA, 1219-1226, July 2006.(R-326):  [pdf]  J. Pearl, “Influence Diagrams–Historical and Personal Perspectives”
UCLA Cognitive Systems Laboratory, Technical Report (R-326), December 2005.
In Decision Analysis, Vol. 2, No. 4, 232-234, December 2005.(R-322):  [pdf]  M. Gallery, M. Hopkins, K. Knight, D. Marcu, “What’s in a Translation Rule?”
UCLA Cognitive Systems Laboratory, Technical Report (R-322), May 2005.
In Proceedings of the Human Language Technology Conference, North American Chapter of the Association for Computational Linguistics (HLTINAACL), Association for Computational Linguistics, East Stroudsburg, PA, 273–280, 2004.(R-321):  [pdf]  C. Avin, I. Shpitser, J. Pearl, “Identifiability of Path-Specific Effects”
UCLA Cognitive Systems Laboratory, Technical Report (R-321), June 2005.
In Proceedings of International Joint Conference on Artificial Intelligence, Edinburgh, Schotland, 357–363, August 2005.
Extended version available (R-321-L).(R-320):  [pdf]  J. Pearl, “Robustness of Causal Claims”
UCLA Cognitive Systems Laboratory, Technical Report (R-320), March 2004.
In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, Banff, Canada, 446-453, July 2004.(R-319):  [pdf]  B. Bonet and S. Thiebaux, “Labeled RTDP: Improving the Convergence of Real-Time Dynamic Programming,”
UCLA Cognitive Systems Laboratory, Technical Report (R-319), June 2003.
In Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling, Trento, Italy, AAAI press, 12–21, 2003.(R-318):   [pdf]  B. Bonet and H. Geffner, “GPT meets PSR,”
UCLA Cognitive Systems Laboratory, Technical Report (R-318), June 2003.
In Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling, Trento, Italy, AAAI press, 102–111, 2003.(R-317):   [pdf]  B. Bonet and H. Geffner, “Faster Heuristic Search Algorithms for Planning with Uncertainty and Full Feedback,”
UCLA Cognitive Systems Laboratory, Technical Report (R-317), August 2003.
In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, Acapulco, Mexico, Morgan Kaufmann, 1233–1238, 2003.(R-316):  [pdf]A. Paz, “A New Graphical Model for the Representative of Marginalized DAG-Representable Relative”
UCLA Computer Science Department, Technical Report (R-316), September 2006.
In Proceedings of the Seventh Workshop on Uncertainty Processing (WUPES’06), Mikulov, Czech Republic, 111–137, September 2006. (R-315):  [pdf]  B. Bonet “Modeling and Solving Sequential Decision Problems with Uncertainty and Partial Information,”  2004.
UCLA Computer Science Department, Technical Report (R-315), January 2004.
Ph.D. Thesis(R-314):   [pdf]  C. Brito “Graphical Methods for Identification in Structural Equation Models,”  2004.
UCLA Computer Science Department, Technical Report (R-314), January 2004.
Ph.D. Thesis(R-313):  [ps] [pdf]M. Hopkins, “LAYERWIDTH: Analysis of a New Metric for Directed Acyclic Graphs,”
UCLA Computer Science Department, Technical Report (R-313), August 2003.
In Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, San Francisco: CA, Morgan Kaufmann Publishers, 321–328, 2003. (R-311):  [ps] [pdf]M. Hopkins and J. Pearl, “Clarifying the Usage of Structural Models for Commonsense Causal Reasoning,”
UCLA Cognitive Systems Laboratory, Technical Report (R-311), January 2003.
In Proceedings of the AAAI Spring Symposium on Logical Formalization of Commonsense Reasoning, AAAI Press, Menlo Park, CA 83–89, 2003.(R-310):  [pdf]  J. Pearl, “Comments on Neuberg’s Review of Causality,”
UCLA Cognitive Systems Laboratory, Technical Report (R-310), December 2002.
In Econometric Theory, Vol. 19, pp. 686-689, 2003.(R-309):   [pdf]
J. Tian “Studies in Causal Reasoning and Learning,”  2002.
UCLA Computer Science Department, Technical Report (R-309), August 2002.
Ph.D. Thesis(R-308):  [pdf]  J. Pearl, “Reply to Woodward,”
UCLA Cognitive Systems Laboratory, Technical Report (R-308), July 2003.
In Economics and Philosophy, Vol. 19, pp. 341-344, 2003.(R-305):  [pdf]J. Tian and J. Pearl, “On the Testable Implications of Causal Models with Hidden Variables,”
UCLA Cognitive Systems Laboratory, Technical Report (R-305), April 2002.
In A. Darwiche and N. Friedman (Eds.), Uncertainty in Artificial Intelligence, Proceedings of the Eighteenth Conference, Morgan Kaufmann: San Francisco, CA, 519–527, August 2002.(R-304):  [pdf]B. Bonet and J. Pearl, “Qualitative MDPs and POMDPs: An Order-of-Magnitude Approximation,”
UCLA Cognitive Systems Laboratory, Technical Report (R-304), April 2002. In A. Darwiche and N. Friedman (Eds.),
Uncertainty in Artificial Intelligence, Proceedings of the Eighteenth Conference, Morgan Kaufmann: San Francisco, CA, 61-68, August 2002.(R-303):  [pdf]C. Brito and J. Pearl, “Generalized Instrumental Variables,”
UCLA Cognitive Systems Laboratory, Technical Report (R-303), April 2002. In A. Darwiche and N. Friedman (Eds.),
Uncertainty in Artificial Intelligence, Proceedings of the Eighteenth Conference, Morgan Kaufmann: San Francisco, CA, 85-93, August 2002.(R-302-A):  [pdf]M. Hopkins and J. Pearl, “Strategies for Determining Causes of Events,”
UCLA Cognitive Systems Laboratory, Technical Report (R-302-A), January 2002.
Proceedings of the Eighteenth National Conference on Artificial Intelligence, AAAI Press/The MIT Press: Menlo Park, CA, 546-552, August 2002.(R-301):  [pdf]M. Hopkins and J. Pearl, “Causality and Counterfactuals in the Situation Calculus,”
UCLA Cognitive Systems Laboratory, Technical Report (R-301), May 2005.
Proceedings of the Seventh International Sympoisum on Logical Formalizations of Commonsense Reasoning, 115-122, 2005.(R-299):   [pdf]  J. Pearl, “Statistics and Causal Inference: A Review”
In Test Journal, Vol. 12(2), pp. 281-345, December 2003 (with discussions).  (R-298):  [pdf]J. Tian and J. Pearl, “A New Characterization of the Experimental Implications of Causal Bayesian Networks,”
UCLA Cognitive Systems Laboratory, Technical Report (R-298), January 2002.
Proceedings of the Eighteenth National Conference on Artificial Intelligence, AAAI Press/The MIT Press: Menlo Park, CA, 574-579, August 2002.(R-297):  [pdf]C. Brito and J. Pearl, “A Graphical Criterion for the Identification of Causal Effects in Linear Models,”
UCLA Cognitive Systems Laboratory, Technical Report (R-297), April 2002.
Proceedings of the Eighteenth National Conference on Artificial Intelligence, AAAI Press/The MIT Press: Menlo Park, CA, 533-538, August 2002.(R-291):  [pdf]C. Brito and J. Pearl, “A new identification condition for recursive models with correlated errors”
UCLA Cognitive Systems Laboratory, Technical Report (R-291), October 2001.
Structural Equation Modeling, 9(4), 459–474, 2002.(R-290-A):  [pdf]J. Tian and J. Pearl, “A General identification condition for causal effects”
UCLA Cognitive Systems Laboratory, Technical Report (R-290-A), April 2001.
Proceedings of the Eighteenth National Conference on Artificial Intelligence, AAAI Press/The MIT Press: Menlo Park, CA, 567-573, August 2002.(R-289): [pdf]J. Pearl, “Causal Inference in Statistics: A Gentle Introduction”
UCLA Cognitive Systems Laboratory, Technical Report (R-289), August 2001.
In Computing Science and Statistics, Proceedings of Interface `01, Volume 33, 2001.(R-285): [postscript] [pdf]J. Tian and J. Pearl, “Causal Discovery from Changes: a Bayesian Approach”
UCLA Cognitive Systems Laboratory, Technical Report (R-285), February 2001.(R-284): [pdf]J. Pearl, “Bayesianism and Causality, or, Why I am Only a Half-Bayesian”
UCLA Cognitive Systems Laboratory, Technical Report (R-284), July 2001.
In D. Corfield and J. Williamson (Eds.) Foundations of Bayesianism,
Applied Logic Series Volume 24, Kluwer Academic Publishers, the Netherlands, 19–36, 2001.(R-283a):  [postscript] [pdf]J. Pearl, “Comments on Seeing and Doing”
UCLA Cognitive Systems Laboratory, Technical Report (R-283-A), February 2001.
In International Statistical Review, 70(2):207-209, 2002.(R-283b):  [postscript] [pdf]J. Pearl, “Comments on Nozer Singpurwalla’s `On Causality and Causal Mechanisms'”
UCLA Cognitive Systems Laboratory, Technical Report (R-283-B), February 2001.
In International Statistical Review, 70(2):210-212, 2002.(R-282):   [pdf]  J. Pearl, “Causal Inference in the Health Sciences: A Conceptual Introduction”
UCLA Cognitive Systems Laboratory, Technical Report (R-282), February 2001.
Health Services and Outcomes Research Methodology, Vol. 2, Special issue on causal inference, Kluwer Academic Publishers, 189–220, 2001.(R-281):   [postscript] [pdf]J. Pearl, “Bayesian Networks, Causal Inference and Knowledge Discovery”
UCLA Cognitive Systems Laboratory, Technical Report (R-281), March 2001.
In Second Moment, March 1, 2001 (R-280):   [postscript], [pdf]  J. Tian and J. Pearl, “Causal Discovery from Changes”
UCLA Cognitive Systems Laboratory, Technical Report (R-280), June 2001.
In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 512-521, 2001.  (R-279):   [postscript] [pdf]  J. Pearl, “On two pseudo-paradoxes in Bayesian analysis”
UCLA Cognitive Systems Laboratory, Technical Report (R-279), February 2001.
Annals of Mathematics and Artificial Intelligence, Special Issue on Representations of Uncertainty, Vol. 32, 171-177, 2001.(R-278):   [postscript] [pdf]J. Pearl, “Exogeneity and Superexogeneity: A No-tear Perspective”
UCLA Cognitive Systems Laboratory, Technical Report (R-278), September 2000.(R-277):   [postscript] [pdf]J. Pearl and S. Russel “Bayesian networks”
UCLA Cognitive Systems Laboratory, Technical Report (R-277), November 2000.
In M.A. Arbib (Ed.), Handbook of Brain Theory and Neural Networks, Cambridge, MA: MIT Press, 157–160, 2003.(R-276):  [postscript] [pdf]  J. Pearl, “Parameter identification: A new perspective”
UCLA Cognitive Systems Laboratory, Technical Report (R-276), January 2001.(R-273-U):  [postscript] [pdf] J. Pearl, “Direct and Indirect Effects”
UCLA Cognitive Systems Laboratory, Technical Report (R-273), June 2001.
In John Breese and Daphne Koller (Eds.), Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 411-420, 2001.
(R-273-JSM):  [pdf]
In Proceedings of the American Statistical Association Joint Statistical Meetings, Minneapolis, MN: MIRA Digital Publishing, 1572–1581, 2005.(R-271-U):   [postscript] [pdf]J. Tian and J. Pearl, “Probabilities of causation: Bounds and identification”
UCLA Cognitive Systems Laboratory, Technical Report (R-271-U), May 2000.
In Craig Boutilier and Moises Goldszmidt (Eds.), Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI-2000), San Francisco, CA: Morgan Kaufmann, 589–598, 2000.
(R-271-A):  [pdf]
Also,  Annals of Mathematics and Artificial Intelligence, Vol. 28, 287–313, 2000.(R-269):  [postscript] [pdf] [reprint]
J. Pearl, “The logic of counterfactuals in causal inference (Discussion of `Causal inference without counterfactuals’ by A.P. Dawid),”
UCLA Cognitive Systems Laboratory, Technical Report (R-269), April 2000.
In Journal of American Statistical Association, Vol. 95, No. 450, 428–431, June 2000.(R-268):  [pdf]
B. Bonet, “A Calculus for Causal Relevance,”
UCLA Cognitive Systems Laboratory, Technical Report (R-268), June 2001.
Proceedings of Conference on Uncertainty in Artificial Intelligence, 40–47, 2001.(R-267):  [pdf]
B. Bonet, “Instrumentality Tests Revisited,”
UCLA Cognitive Systems Laboratory, Technical Report (R-267), June 2001.
Proceedings of Conference on Uncertainty in Artificial Intelligence, 48–55, 2001.(R-266-UAI):  [pdf]J.Y. Halpern and J. Pearl, “Causes and explanations: A structural-model approach—Part I:  Causes”
UCLA Cognitive Systems Laboratory, Technical Report (R-266-UAI), November 2000.
In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence,
San Francisco, CA: Morgan Kaufmann, 194–202, 2001.  
(R-266-BJPS1): [pdf]
Also in British Journal of Philosophy of Science 56:843-887, 2005.(R-266-IJCAI):  [pdf]J.Y. Halpern and J. Pearl, “Causes and explanations: A structural-model approach—Part II: Explanations”
UCLA Cognitive Systems Laboratory, Technical Report (R-266-IJCAI), November 2000.
In Proceedings of IJCAI, San Francisco, CA: Morgan Kaufmann, 2001.
(R-266-BJPS2): [pdf]
Also in British Journal of Philosophy of Science 56:889-911, 2005. (R-265):   [pdf]J. Pearl, “Reasoning with cause and effect”
UCLA Cognitive Systems Laboratory, Technical Report (R-265), July 1999.
In AI Magazine, Vol. 23(1), 95-111, Spring 2002.
(R-265-I-Transcript): [pdf]
Transcript of lecture given at the International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, Sweden, on 4 August 1999.(R-264):  [postscript] [pdf]J. Pearl, “Simpson’s paradox: An anatomy”
UCLA Cognitive Systems Laboratory, Technical Report (R-264), November 1999.(R-263):  [pdf]
J. Pearl, “Statistics, Causality, and Graphs”
UCLA Cognitive Systems Laboratory, Technical Report (R-263), September 1999.
In A. Gammerman (Ed.), Causal Models and Intelligent Data Management, Chapter 1, Germany: Springer-Verlag, pp. 3-16, 1999.(R-260):   [pdf]J. Pearl, “Probabilities of Causation: Three Counterfactual Interpretations and their identification”
UCLA Cognitive Systems Laboratory, Technical Report (R-260), September 1998.
In Synthese, Vol. 121, 93-149, 1999.(R-257):  [pdf]J. Pearl and P. Meshkat, “Testing regression models with fewer regressors”
UCLA Cognitive Systems Laboratory, Technical Report (R-257), August 1998.
In Proceedings of AI-Stat, 255–259, 1999. (R-256):   [postscript] [pdf]J. Pearl, “Why there is no statistical test for confounding, why many think there is, and why they are almost right”
UCLA Cognitive Systems Laboratory, Technical Report (R-256), January 1998.
Incorporated into Chapter 6 of Causality(R-254):   [pdf]
J. Tian, A. Paz, J. Pearl, “Finding a minimal d-separator”
UCLA Cognitive Systems Laboratory, Technical Report (R-254), February 1998.
(R-253):   [pdf]J. Pearl, “Graphs, Causality, and Structural Equation Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-253), June 1998.
Sociological Methods and Research, Vol. 27, No. 2, 226-284, November 1998.(R-252):   [pdf]S. Greenland, J.M. Robins, and J. Pearl, “Confounding and collapsibility in causal inference,”
UCLA Cognitive Systems Laboratory, Technical Report (R-252), December 1998.
Statistical Science, Volume 14, No. 1, pp. 29-46, 1999.(R-251):   [pdf]S. Greenland, J. Pearl, and J.M. Robins, “Causal Diagrams for Epidemiologic Research,”
UCLA Cognitive Systems Laboratory, Technical Report (R-251), January 1999.
Epidemiology Journal, Volume 10, No. 10, pp. 37-48, 1999.(R-250):   [postscript] [pdf]D. Galles and J. Pearl, “An Axiomatic Characterization of Causal Counterfactuals”
UCLA Cognitive Systems Laboratory, Technical Report (R-250), September 1997.
Foundations of Science, Volume 3, Issue 1 1998, pp. 151 – 182, Kluwer Academic Publishers, 1998.(R-249):   [postscript] [pdf]J. Pearl, “The New Challenge: From a Century of Statistics to the Age of Causation”
UCLA Cognitive Systems Laboratory, Technical Report (R-249), January 1997.
Presented at the IASC Second World Congress, Pasadena, CA, February 1997.(R-248):   [transcript] [pdf]J. Pearl, “The Art and Science of Cause and Effect”
UCLA Cognitive Systems Laboratory, Technical Report (R-248), October 1996.  
Transcript of lecture given Thursday, October 29, 1996, as part of the UCLA 81st Faculty Research Lecture Series(R-246):   [postscript] [pdf]J. Pearl, “Bayesian Networks”
UCLA Cognitive Systems Laboratory, Technical Report (R-246), Revision I, July 1997.
In MIT Encyclopedia of the Cognitive Sciences, Cambridge, MA, 1999.(R-245):  Request hard copyD.M. Chickering, “Learning Bayesian Networks from Data,”
UCLA Cognitive Systems Laboratory, Technical Report (R-245), June 1996.
Ph.D. Thesis(R-244-S):  [postscript] [pdf]J. Pearl, “On the Foundation of Structural Equation Models or When Can We Give Causal Interpretation to Structural Coefficients?”
UCLA Cognitive Systems Laboratory, Technical Report (R-244-S), November 1996.
Portions of this report are included in a commentary prepared for Multivariate Behavioral Research.(R-244):   [postscript] [pdf]J. Pearl, “TETRAD and SEM”
UCLA Cognitive Systems Laboratory, Technical Report (R-244), June 1998.
Commentary on “TETRAD Project: Constraint Based Aids to Causal Model Specification” by R. Scheines, P. Spirtes, C. Glymour, C. Meek, and T. Richardson.
In Multivariate Behavioral Research, 33(1), 119–128, 1998.(R-243):   [postscript] [pdf]J. Pearl and R. Dechter, “Identifying Independencies in Causal Graphs with Feedback”
UCLA Cognitive Systems Laboratory, Technical Report (R-243), March 1996
In E. Horvitz and E. F. Jensen (Eds.), Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann: San Francisco, CA, 420–426, August 1996.(R-242):    Request hard copyA. Balke, “Probabilistic Counterfactuals: Semantics, Computation, and Applications,”
UCLA Cognitive Systems Laboratory, Technical Report (R-242), November 1995.
Ph.D. Thesis(R-241):  [postscript] [pdf]D.M. Chickering and J. Pearl, “A Clinician’s Apprentice for Analyzing Non-compliance,”
UCLA Cognitive Systems Laboratory, Technical Report (R-241), January 1996
In Proceedings of the National Conference on Artificial Intelligence (AAAI-96), Portland, OR, 1269–1276, August 1996.
Also in Chickering, D. M. and Pearl, J. (1997) “A clinician’s tool for analyzing non-compliance,” Computing Science and Statistics, 29(2), 424-431, 1997.
(R-240):   [pdf]D. Galles and J. Pearl, “Axioms of Causal Relevance”
UCLA Cognitive Systems Laboratory, Technical Report (R-240), January 1996
In Artificial Intelligence, 97(1-2), 9–43, 1997(R-240-S):   [pdf]D. Galles and J. Pearl, “Axioms of Causal Relevance”
UCLA Cognitive Systems Laboratory, Technical Report (R-240-S), January 1996.
Preliminary version in Proceedings of the Fourth International Conference on Mathematics and AI, Fort Lauderdale, FL, 64–67, January 1996.(R-238):   [postscript] [pdf]  J. Pearl, “Covariate Selection: A Simple Solution To a Long-Standing Problem”
UCLA Cognitive Systems Laboratory, Technical Report (R-238).
In American Statistical Association 1996 Proceedings of the Section on Bayesian Statistical Science, Chicago, IL, pp. 162–163, August 2-3, 1996.(R-237):  [postscript] [pdf] J. Pearl, “Structural and Probabilistic Causality”
UCLA Cognitive Systems Laboratory, Technical Report (R-237).
In D.R. Shanks, K.J. Holyoak, and D.L. Medin (Eds.), The Psychology of Learning and Motivation, Vol. 34: Causal Learning, Academic Press, San Diego, CA 393-435, 1996.(R-236):   [pdf]J. Pearl, “Graphical Models for Probabilistic and Causal Reasoning”
UCLA Cognitive Systems Laboratory, Technical Report (R-236).
In A.B. Tucker, Jr. (Ed.), The Computer Science and Engineering Handbook, Chapter 31, CRC Press, Inc. 697–714, 1997.
In A.B. Tucker, Jr. (Ed.), Computer Science Handbook, 2nd Edition, Chapter 70, CRC Press, pp. 70-1 — 70-18, 2004.
In A. Tucker, T. Gonzalez, H. Topi, J. Diaz-Herrera (Eds.) Computing Handbook (Renamed), Third Edition, Volume 1, Intelligent Systems section, Chapman and Hall/CRC, 2014.(R-232-U):   [postscript] [pdf]A. Balke and J. Pearl, “Counterfactuals and Policy Analysis in Structural Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-232-U).
In P. Besnard and S. Hanks (Eds.), Uncertainty in Artificial Intelligence 11, Morgan Kaufmann, San Francisco, CA, 11-18, 1995.(R-226-U):   [postscript] [pdf]D. Galles and J. Pearl, “Testing Identifiability of Causal Effects,”
UCLA Cognitive Systems Laboratory, Technical Report (R-226-U).
In P. Besnard and S. Hanks (Eds.), Uncertainty in Artificial Intelligence 11, Morgan Kaufmann, San Francisco, CA, 185-195, 1995.(R-223-U):   [postscript] [pdf]J. Pearl, “Causation, action, and counterfactuals,”
UCLA Cognitive Systems Laboratory, Technical Report (R-223-U).
Presented at UNICOM Seminar, London, April 3-5, 1995.
In A. Gammerman (Ed.), Computational Learning and Probabilistic Reasoning, John Wiley and Sons, New York, Chapter, 15, 235-255, 1995.(R-223-T):   [postscript] [pdf]
UCLA Cognitive Systems Laboratory, Technical Report (R-223-T).
In Y. Shoham (Ed.), Theoretical Aspects of Rationality and Knowledge, Proceedings of the Sixth Conference (TARK 1996) The Netherlands, 51–73, March 17-20, 1996.(R-219-U):   [postscript] [pdf]J. Pearl and James Robins, “Probabilistic Evaluation of Sequential Plans from Causal Models with Hidden Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-219-U).
In P. Besnard and S. Hanks (Eds.), Uncertainty in Artificial Intelligence 11, Morgan Kaufmann, San Francisco, CA, 444-453, 1995.(R-218-B-L):   [postscript] [pdf]J. Pearl, “Causal diagrams for empirical research,”
UCLA Cognitive Systems Laboratory, Technical Report (R-218-B-L), January 1996.
Expanded version of a paper in Biometrika, 1995 (R-218-B).(R-218-B):   [postscript] [pdf]J. Pearl, “Causal Diagrams for Empirical Research,”
UCLA Cognitive Systems Laboratory, Technical Report (R-218-B).
In Biometrika, Vol. 82, No. 4, 669-709, December 1995.(R-217):   [postscript] [pdf]J. Pearl, “Three Statistical Puzzles”
UCLA Cognitive Systems Laboratory, Technical Report (R-217), Revision I, May 1994.(R-216):   [pdf]J. Pearl, and S. Russell “Bayesian Networks”
UCLA Cognitive Systems Laboratory, Technical Report (R-216), Revision I.
In M. Arbib (Ed.), Handbook of Brain Theory and Neural Networks,  Second Edition, Cambridge, MA: MIT Press, 157-160, 2003.(R-215):   [pdf] [bib]D. Geiger, A. Paz, and J. Pearl, “On testing whether an Embedded Bayesian Network represents a probability model”
UCLA Cognitive Systems Laboratory, Technical Report (R-215)
In R. Lopez de Mantaras and D. Poole (Eds.), Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI-94), Morgan Kaufman, San Mateo, CA, 454-462, 1994. (R-214):   [pdf]S-W. Tan and J. Pearl, “Qualitative Decision Theory”
UCLA Cognitive Systems Laboratory, Technical Report (R-214)
In Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI Press/TheMIT Press, 928-933, 1994.(R-213-A):   [postscript] [pdf]A. Balke and J. Pearl, “Probabilistic Evaluation of Counterfactual Queries”
UCLA Cognitive Systems Laboratory, Technical Report (R-213-A)
In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, Volume I, 230-237, July 31 – August 4, 1994.(R-213-B):   [postscript] [pdf]A. Balke and J. Pearl, “Counterfactual Probabilities: Computational Methods,Bounds, and Applications”
UCLA Cognitive Systems Laboratory, Technical Report (R-213-B).
In R. Lopez de Mantaras and D. Poole (Eds.), Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI-94), Morgan Kaufmann, San Mateo, CA, 46-54, July 29-31, 1994. (R-212):   [pdf] [bib]J. Pearl, “A Probabilistic Calculus of Actions”
UCLA Cognitive Systems Laboratory, Technical Report (R-212).
In R. Lopez de Mantaras and D. Poole (Eds.), Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI-94), Morgan Kaufman, San Mateo, CA, 454-462, 1994.(R-211-U):   [postscript] [pdf]J. Pearl, “On the Testability of Causal Models with Latent and Instrumental Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-211-U)
In P. Besnard and S. Hanks (Eds.), Uncertainty in Artificial Intelligence 11, Morgan Kaufmann, San Francisco, CA, 435-443, 1995.(R-211-S):   [postscript] [pdf]J. Pearl, “A Note on Testing Exogeneity of Instrumental Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-211-S), Revision I.(R-210):   [postscript] [pdf]J. Pearl, “Mediating Instrumental Variables”
UCLA Cognitive Systems Laboratory, Technical Report (R-210).(R-207):   [postscript] [pdf]J. Pearl, “On the Identification of Nonparametric Structural Models”
UCLA Cognitive Systems Laboratory, Technical Report (R-207), Revised March 1997.
In M. Berkane (Ed.), Latent Variable Modelling with Application to Causality, Springer Verlag, Lecture Notes in Statistics, 29-68, 1997.(R-206):   [postscript] [pdf]A. Darwiche and J. Pearl, “Symbolic Causal Networks for Reasoning about Actions and Plans”
UCLA Cognitive Systems Laboratory, Technical Report (R-206)
In Symposium Notes of the 1994 AAAI Spring Symposium on Decision-Theoretic Planning, 41-47, March 21-23, 1994.
Also in Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, Volume I, 238-244, July 31 – August 4, 1994.(R-203-L):   [pdf]J. Pearl, “Causal Inference from Indirect Experiments”
UCLA Cognitive Systems Laboratory, Technical Report (R-203-L).
In Symposium Notes of the 1994 AAAI Spring Symposium on Artificial Intelligence in Medicine, Stanford, CA, March 1994.
(R-203-AIM):   [pdf] Extended version in Artificial Intelligence in Medicine Journal, Vol. 7, No. 6, 561-582, 1995.(R-202):    [postscript] [pdf]A. Darwiche and J. Pearl, “On the Logic of Iterated Belief Revision”
UCLA Cognitive Systems Laboratory, Technical Report (R-202).
In R. Fagin (Ed.), Proceedings of the 1994 Conference on Theoretical Aspects of Reasoning about Knowledge (TARK `94), Pacific Grove, CA, 5-23, March 13-16, 1994.
Also in Artificial Intelligence, 89(1-2):1–29, 1997.(R-200):   [postscript] [pdf]J. Pearl, “On the Statistical Interpretation of Structural Equations”
UCLA Cognitive Systems Laboratory, Technical Report (R-200).(R-199-J):   [pdf]A. Balke and J. Pearl, “Bounds on Treatment Effects from Studies with Imperfect Compliance”
UCLA Cognitive Systems Laboratory, Technical Report (R-199-J).
In Journal of the American Statistical Association  Vol. 92, 1171-1176, 1997.(R-199-A):   [postscript] [pdf]A. Balke and J. Pearl, “Universal Formulas for Treatment Effects from Noncompliance Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-199-A).
In N.P. Jewell, A.C. Kimber, M.-L. Lee, and G.A. Whitmore (Eds.), Lifetime Data: Models in Reliability and Survival Analysis, Kluwer Academic Publishers, Dordrecht, 39-43, 1995.(R-199):   [postscript] [pdf]A. Balke and J. Pearl, “Nonparametric Bounds on Causal Effects from Partial Compliance Data”
UCLA Cognitive Systems Laboratory, Technical Report (R-199).(R-197):   [pdf]A. Paz, J. Pearl, and S. Ur, “A New Characterization of Graphs Based on Interception Relations”
UCLA Cognitive Systems Laboratory, Technical Report (R-197).
Journal of Graph Theory, Vol. 22, No. 2, 125-136, 1996.(R-195-LLL):   [postscript] [pdf]J. Pearl, “From Bayesian Networks to Causal Networks”
UCLA Cognitive Systems Laboratory, Technical Report (R-195-LLL)
In A. Gammerman (Ed.) Bayesian Networks and Probabilistic Reasoning, Alfred Walter Ltd., London, 1-31, 1994.(R-195-LL):   [postscript] [pdf]J. Pearl, “Aspects of Graphical Models Connected With Causality,”
UCLA Cognitive Systems Laboratory, Technical Report (R-195-LL).
In Proceedings of the 49th Session of the International Statistical Institute, Italy, Tome LV, Book 1, Florence, 399-401, August 1993.(R-195-SS):   [pdf]J. Pearl, “Graphical Models, Causality, and Intervention”
[Comments on: `Linear Dependencies Represented by Chain Graphics’ by D. Cox and N. Wermuth, and `Bayesian Analysis in Expert Systems’ by D.J. Spiegelhalter, A.P. Dawid, S.L. Lauritzen, and R.G. Cowell]
UCLA Cognitive Systems Laboratory, Technical Report (R-195-SS).
In Statistical Science, Vol. 8, 266-269, 1993.(R-192):   [postscript] [pdf]J. Pearl, “A Calculus of Pragmatic Obligation”
UCLA Cognitive Systems Laboratory, Technical Report (R-192).
Presented at the AAAI Spring Symposium on Reasoning about Mental States, Stanford, CA March 23-25, 1993.(R-191):   [pdf]T.S. Verma “Graphical Aspects of Causal Models”  UCLA Cognitive Systems Laboratory, Technical Report (R-191), Draft Copy, January 1993.(R-190):   [pdf]M. Goldszmidt “Qualitative Probabilities: A Normative Framework for Commonsense Reasoning”
UCLA Cognitive Systems Laboratory, Technical Report (R-190) , Ph.D. Thesis(R-185):   [pdf]D. Dor and M. Tarsi, “A simple algorithm to construct a consistent extension of a partially oriented graph”
UCLA Cognitive Systems Laboratory, Technical Report (R-185), October 1992.(R-183):   [postscript] [pdf]J. Pearl and N. Wermuth, “When Can Association Graphs Admit A Causal Explanation?”
UCLA Cognitive Systems Laboratory, Technical Report (R-183).
In Proceedings of the Fourth International Workshop on Artificial Intelligence and Statistics, 141-150, January 1993.
Also in P. Cheeseman and W. Oldford (Eds.), Selecting Models and Data, Artificial Intelligence and Statistics IV, Springer-Verlag, 205-214, 1994.(R-178):   [pdf]M Goldsmidt and J. Pearl, “Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions”
UCLA Cognitive Systems Laboratory, Technical Report (R-178).
In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR`92), Morgan Kaufmann, San Mateo, CA, 661-672, 1992.(R-177):   [postscript] [pdf]T.S. Verma and J. Pearl, “An Algorithm for Deciding if a Set of Observed Independencies has a  Causal Explanation”
UCLA Cognitive Systems Laboratory, Technical Report (R-177).
In Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence), Morgan Kaufmann, San Mateo, CA, 323-330, July 1992.(R-175):   [pdf]J. Pearl, “Belief Networks Revisited”
UCLA Cognitive Systems Laboratory, Technical Report (R-175).
In Artificial Intelligence, 59, 49-56, 1993. [Invited submission — Special Issue, “AI in Perspective”](R-174):   [pdf]R. Dechter, and I. Meiri, “Experimental evaluation of constraint processing”
UCLA Cognitive Systems Laboratory, Technical Report (R-174), January 1992.(R-173):   [pdf]I. Meiri, “Temporal Reasoning: A Constraint-Based Approach,”
UCLA Cognitive Systems Laboratory, Technical Report (R-173), January 1992. Ph.D. Thesis.(R-172):   [pdf]R. Dechter and J. Pearl, “Structure identification in relational data,”
UCLA Cognitive Systems Laboratory, Technical Report (R-172), June 1992. Artificial Intelligence 58:237-270, 1992.
(R-172-S):   [pdf]R. Dechter and J. Pearl, “Structure identification in relational data,” In Procdeedings of the Candian AI Conference, Vancouver, Canada, 176-189, January 1992.

R-171 Goldszmidt, M. & Pearl, J., “Stratified Rankings for Causual Modeling,”

R-170-S Ben-Eliyahu, R. & Dechter, R., “Propositional Semantics for Dis…”
R-170-L Ben-Eliyahu, R. & Dechter, R., “Propositional Semantics for Dis…”

R-169 Ben-Eliyahu, R. & Dechter, R., “Translating a Cycle Default Theory…”

R-168 Pearl, J. & Dechter, R. & Verma, T., “Knowledge Discovery VS. Data…”

R-167 Collin, Z. & Dechter, R. & Katz, S., “On the Feasibility of Dist…”

R-166 Dalkey, N. “Webs,”

R-165 Dalkey, N. “Tree Extensions of Graphical Structures,”

R-164 Dalkey, N. “Entropy and Belief Networks,”

R-163-II Ben-Eliyahu, R. & Dechter, R., “Default Reasoning Using Classi…”
R-163 Ben-Eliyahu, R. & Dechter, R., “Propositional Semantics for Def…”

R-162 Ben-Eliyahu, R. & Dechter, R., “Default Logic, Propositional Log…”

(R-161-L):   [pdf]M. Goldszmidt and J. Pearl, “Qualitative Probabilities for Default Reasoning, Belief Revision, and Causal Modeling”
UCLA Cognitive Systems Laboratory, Technical Report (R-161-L).
In Artificial Intelligence, Vol. 84, No. 1-2, 57–112, 1996.(R-156):   [pdf]J. Pearl and T.S. Verma, “A Theory of Inferred Causation” 
UCLA Cognitive Systems Laboratory, Technical Report (R-156)
In J.A Allen, R. Fikes, and E. Sandewall (Eds.), Principles of Knowledge Representation and Reasoning: Proceeding of the Second International Conference, San Mateo, CA: Morgan Kaufmann, 441-452, April 1991.
A modified version was presented at the Ninth International Congress of Logic, Methodology, and Philosophy of Science, Uppsala, Sweden, August 7-14, 1991 and printed in D. Prawitz, B. Skyrms, and D. Westerstahl (Eds.), Logic, Methodology and Philosophy of Science IX, Elsevier Science B.V., 789–811, 1994.(R-155):   [postscript] [pdf]J. Pearl and T.S. Verma, “A Statistical Semantics for Causation” 
UCLA Cognitive Systems Laboratory, Technical Report (R-155).
In Proceeding, 3rd International Workshop on Artificial Intelligence and Statistics (AISTATS), Fort Lauderdale, FL, January 2-5, 1991.
Also in Statistics and Computing, 2, Chapman and Hall, 91-95, 1992.

 

(R-154). M. Goldszmidt and J. Pearl. “Where do Default Priorities Come From?,” UCLA Cognitive Systems Laboratory, Computer Science Department, Technical Report (R-154), November, 1990.

(R-153). R. Dechter and J. Pearl. “Directed Constraint Networks: A Relational Framework for Causal Modeling,” UCLA Cognitive Systems Laboratory, Technical Report CSD-910023 (R-153), December, 1990, in Proceedings, 12th International Joint Conference of Artificial Intelligence (IJCAI-91), Sydney, Australia, 1164-1170, August 24-30, 1991,

(R-152). D. Geiger, A. Paz and J. Pearl. “Learning Simple Causal Networks.” UCLA Cognitive Systems Laboratory, Technical Report (R-152), September, 1990. In International Journal of Intelligent Systems, John Wiley and Sons, Inc., Vol. 8, 231-247, 1993.

(R-151). I. Meiri and J. Pearl. “Faster Constraint Satisfaction Algorithms for Temporal Reasoning.” UCLA Cognitive Systems Laboratory, Computer Science Department, Technical Report (R-151), July, 1990.

(R-150). T. Verma & J. Pearl. “Equivalence and Synthesis of Causal Models.” UCLA Cognitive Systems Laboratory, Technical Report (R-150), June 1990, in Proceedings, Workshop on Uncertainty in Artificial Intelligence, July 27-29, 1990. Also in Uncertainty in Artificial Intelligence, 6, Cambridge, MA, Elsevier Science Publishers, 220-227, 1991.

(R-149). D. Geiger, A. Paz & J. Pearl. “Learning Causal Trees from Dependence Information.” UCLA Cognitive Systems Laboratory Technical Report (R-149), February 1990, in Proceedings, AAAI-90, Boston, MA, 770-776, 7/29-8/3/90.

(R-148). Z. Collin & R. Dechter, “A Distributed Solution to the Network Consistency Problem.” Technical Report (R-148), March 1990, in Proceedings, ISMIS-90, Lennox, TN, 1990.

(R-147). R. Dechter, “On the Expressiveness of Networks with Hidden Variables.” Technical Report (R-147), February 1990, in Proceedings, AAAI-90, Boston, MA, 556-562, 7/29-8/3/90.

(R-146). I. Meiri, R. Dechter, & J. Pearl, “Tree Decomposition with Application to Constraint Processing.” Cognitive Systems Laboratory, Technical Report CSD-910037 (R-146), February 1990, in Proceedings, AAAI-90, Boston, MA, 10-16, 7/29-8/3/90.

(R-145). J. Pearl, “Probabilistic and Qualitative Abduction.” Cognitive Systems Laboratory, Technical Report CSD-910042 (R-145), February 1990, in Proceedings, AAAI Spring Symposium on Automated Abduction, Stanford, CA, 155-158, March 27-29, 1990.

(R-144). M. Goldszmidt, P. Morris, & J. Pearl, “A Maximum Entropy Approach to Nonmonotonic Reasoning.” Technical Report CSD-910041 (R-144), February 1990. Revised 5/90 short version in Proceedings, AAAI-90, Boston, MA, 646-652, 7/29-8/3/90.
Also in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 3, 220-232, March 1993.

(R-143). J. Pearl, “Which is More Believable, The Probably Provable or the Provably Probable?” Technical Report CSD-910040 (R-143), March 1990, in Proceedings, CSCSI-90, Eighth Canadian Conference on Artifical Intelligence, Ottawa, CA, May 23-25, 1-7, 1990.

(R-142). D. Geiger, “Graphoids: A Qualitative Framework for Probabilistic Inference,” UCLA Cognitive Systems Laboratory, Technical Report (R-142), PhD. Dissertation, January 1990.

(R-141). D. Geiger & D. Heckerman, “Practical and Theoretical Advances in Knowledge Acquisition of Probabilistic Networks,” Technical Report (R-141), January 1990, in Proceedings, Workshop on Uncertainty and Probability in Artificial Intel ligence, July 27-29, 1990. Also in Uncertainty in Artificial Intelligence, 6, Cambridge, MA, 538-545, 1991, (entitled “Separable and Transitive Graphoids”).

(R-140). D. Geiger, A. Paz and J. Pearl, “Identifying Polytrees of Compositional Graphoids.” UCLA Cognitive Systems Laboratory Technical Report (R-140), December 1989.(SEE R-149 NEW VERSION)

(R-139). G. Goldszmidt & J. Pearl, “On the Relation Between Rational Closure and System-Z.” UCLA Cognitive Systems Laboratory, Technical Report CSD-910043 (R-139), May, 1990, in Proceedings of the Third International Workshop on Nonmonotonic Reasoning, S. Lake Tahoe, CA, 130-140, May 31-June 3, 1990.

(R-138). R. Dechter & A. Dechter, “Structure-Driven Algorithms for Truth Maintenance.” UCLA Cognitive Systems Laboratory, Technical Report CSD-910045 (R-138), February 1990. Submitted to Artificial Intelligence, August 1994. Artificial Intelligence 82:1-20, 1996.

(R-137). H. Geffner, “Default Reasoning: Causal and Conditional Theories.” UCLA Cognitive Systems Laboratory, Technical Report (R-137), CSD #890065, PhD. Dissertation, November 1989.

(R-136). J. Pearl, “Reasoning with Belief Functions: An Analysis of Compatibility.” Technical Report CSD-910047 (R-136). In The International Journal of Approximate Reasoning, Vol. 4, No. 5/6, 363-389, 1990.

(R-136-REJOINDER). J. Pearl, “Rejoinder to Comments on `Reasoning with Belief Functions: An Analysis of Compatibility'” International Journal of Approximate Reasoning, Vol. 6, No. 3, 425-443, 1992.
Link to all articles in this issue

Dalkey, N. 1976. “Group Decision Analysis,” in M. Zeleny (Ed.), Multi-Criteria Decision Making, Springer-Verlag, The Netherlands, 1976.

(R-135). R. Dechter, “From Local to Global Consistency,” UCLA Cognitive Systems Laboratory, Technical Report CSD-910046 (R-135), September 1989, in Proceedings, Eighth Canadian Conference on Artificial Intelligence, CSCSI-90, 231-237, May 23-25, 1990, “Best Paper Award.” Also in Artificial Intelligence, 55, Elsevier Science Publishers, 87-107, 1992.

(R-132). J. Pearl & R. Dechter, “Learning Structure from Data: A Survey.” UCLA Cognitive Systems Laboratory, Technical Report CSD-910048 (R-132), June 1989. in Proceedings, 2nd Workshop on Computational Learning Theory (COLT’89), Santa Cruz, CA, 230-244, August 1989.

(R-131). J. Pearl, “System Z: A Natural Ordering of Defaults with Tractable Applications to Nonmonotonic Reasoning.” UCLA Cognitive Systems Laboratory, Technical Report CSD-910049 (R-131), December 1989. In R. Parikh (Ed.), Theoretical Aspects on Reasoning about Knowledge, San Mateo, CA: Morgan Kaufmann, 121-135, 1990.

(R-130). D. Geiger, T. Verma & J. Pearl, “d-Separation: From Theorems to Algorithms.” UCLA Cognitive Systems Laboratory, Technical Report CSD-890040 (R-130), March 1989, in Proceedings, Fifth Annual Conference on Uncertainty in Artificial Intelligence, Windsor, Ontario, Canada, 118-125, August 1989. Also in M. Henrion, R.D. Shachter, L.N. Kanal, & J.F. Lemmer (Eds.), Uncertainty in AI, 5, Elsevier Science Publishers (North Holland), 139-148, 1990.

(R-129). H. Geffner & T. Verma, “Inheritance = Chaining + Defeat.” UCLA Cognitive Systems Laboratory, Technical Report CSD-890039 (R-129), March 1989. A condensed version (R-129-S) in Z. Ras (Ed.), Methodologies for Intelligent Systems, IV., New York: Elsevier Science Publishing Co. 1989. A compilation of papers presented at the 4th Intl. Symposium on Methodologies for Intelligent Systems (ISMIS’89), Charlotte, North Carolina, 411-418, Fall 1989.

(R-128-KR). J. Pearl, “Probabilistic Semantics for Nonmonotonic Reasoning: A Survey.” UCLA Cognitive Systems Laboratory, Technical Report CSD-890038 (R-128), February 1989, in Proceedings, First Intl. Conf. on Principles of Knowledge Representation and Reasoning, Toronto, Canada, 505-516, May 1989.

(R-128). J. Pearl, “Probabilistic Semantics for Nonmonotonic Reasoning.”
Expanded version in Robert Cummins and John Pollock (Eds.), Philosophy and AI – Essays at the Interface, Bradford Books/MIT Press, 157-187, 1991.

(R-125). H. Geffner, “Default Reasoning, Minimality and Coherence,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890037 (R-125), February 1989, in Proceedings, First International Conference on Principles of Knowledge Representation and Reasoning (KR’89), Toronto , Canada, 137-148, May 1989.

(R-124). J. Pearl, “Locality-Bounded Rationality,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890036 (R-124), February 1989. in Proceedings, AAAI-89 Spring Symposium, Stanford, CA, 92-95, March 1989.

(R-123). D. Geiger & J. Pearl, “Logical and Algorithmic Properties of Independence and Their Application to Bayesian Networks,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890035 (R-123), July 1989. In Annals of Mathematics and AI, (Special Issue on Statistics and AI), Vol. 2, No. 1-4, 165-178, 1990.

(R-122). M. Goldszmidt & J. Pearl, “Deciding Consistency of Databases Containing Defeasible and Strict Information,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890034 (R-122), February 1989, in Proceedings, 5th Workshop on Uncertainty in AI, Windsor, Ontario, Canada, 134-141, August 1989. Also in M. Henrion, R.D. Shachter, L.N. Kanal, and J.F. Lemmer (Eds.). Uncertainty in Artificial Intelligence, 5, Elsevier Science Publishers B.V. (North Holland), 87-97, 1990.
(R-122-AI). M. Goldszmidt & J. Pearl, “On the consistency of defeasible databases*,” Artificial Intelligence, North-Holland Publishers, Amsterdam, (52), 121-149, December 1991.

(R-121). R. Dechter & I. Meiri, “Experimental Evaluation of Preprocessing Techniques in Constraint-Satisfaction Problems,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890033 (R-121), December 1988, in Proceedings, IJCAI-89, Detroit, MI, 271-277, August 1989.
(R-121-AI). R. Dechter & I. Meiri, “Experimental evaluation of preprocessing algorithms for constraint satisfaction problems,”
Artificial Intelligence, Elsevier Science B.V., Vol. 68, 211–241, 1994.

(R-120). R. Dechter & A. Dechter, “Constraint Based Truth-Maintenance and It’s Application to Diagnosis,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890032 (R-120), December 1988, in Proceedings, 5th Israeli Symposium on AI, Tel-Aviv, Israel, 2-15, December 1988.

(R-119). D. Geiger, A. Paz & J. Pearl, “Axioms and Algorithms for Inferences Involving Probabilistic Independence,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890031 (R-119), December l988. In Information and Computation, Vol. 91, No. 1, 128-141, March 1991.

(R-118). A. Paz & R. Schulhoff, “Closure Algorithms and Decision Problems for Graphoids Generated by Two Undirected Graphs – Abridged Version,” UCLA Cognitive Systems Laboratory, Technical Report 880096 (R-118), September 1988.

Pearl, J. Probabilistic Reasoning in Intelligent Systems, San Mateo: Morgan Kaufmann, 1988.

(R-117). A. Paz, “Membership Algorithm for Marginal Independencies,” UCLA Cognitive Systems Laboratory, Technical report 880095 (R-117), September 1988.

(R-116). D. Geiger, Verma, T.S. & Pearl, J., “Identifying Independence in Bayesian Networks,” UCLA Cognitive Systems Laboratory, Technical Report CSD-890028 (R-116). In Networks, Vol. 20, No. 5, 507-534, 1990.

(R-115). Verma, T.S., & D. Geiger, “On the Membership Problem in Semi-Graphoids,” UCLA Cognitive Systems Laboratory, Technical Report (R-115). In preparation.

(R-114). Pearl, J., D. Geiger & T. Verma, “The Logic of Influence Diagrams,” UCLA Cognitive Systems Laboratory, Technical Report 880061 (R-114), April 1988, in Proceedings, Conference on Influence Diagrams for Decision Analysis, Inference, and Prediction, Berkeley, CA, May 1988.
(R-114-II)Also in R.M. Oliver and J.Q. Smith (Eds.), Influence Diagrams, Belief Nets and Decision Analysis, Sussex, England: John Wiley & Sons, Ltd., 67-87, 1989.
(R-114-S)A shorter version, (R-114-S), in Kybernetika, Vol. 25:2, 33-44, 1989.

(R-113). Dechter, R., I. Meiri, & J. Pearl, “Temporal Constraint Networks,” UCLA Cognitive Systems Laboratory, Technical Report (R-113), February 1989, in Proceedings, First International Conference on Principles of Knowledge Representation and Reasoning (KR’89), Toronto, Canada, 83-93, May 1989. An extended version (R-113-L) in special issue of Artificial Intelligence, Vol. 49, 61-95, 1991.

(R-112). Geiger, D., & J. Pearl, “On the Logic of Causal Models,” UCLA Cognitive Systems Laboratory, Technical Report 880060 (R-112), March 1988, in Proceedings, 4th Workshop on Uncertainty in Artificial Intelligence, Minneapolis, MN, Mountain View, CA: Advanced Decision Systems, 136-147, August 1988. Also in L. Kanal, T. Levitt & R. Shachter (Eds.), Uncertainty in Artificial Intelligence 4, Amsterdam: North-Holland Publishing Co., 3-14, 1990.

(R-111). Dechter, R., A. Dechter & J. Pearl, “Optimization in Constraint Networks,” UCLA Cognitive Systems Laboratory, Technical Report 880059 (R-111), March 1988, in Proceedings, Conference on Influence Diagrams for Decision Analysis, Inference, and Prediction, Berkeley, CA, May 1988. Also in R.M. Oliver and J.Q. Smith (Eds.), Influence Diagrams, Belief Nets and Decision Analysis, Sussex, England: John Wiley & Sons, Ltd., 411-425, 1989.

(R-110). Geffner, H., “On the Logic of Defaults,” UCLA Cognitive Systems Laboratory, Technical Report 880058 (R-110), March 1988, in Proceedings, AAAI-88, St. Paul, MN, 449-454, August 1988.

(R-109). Dechter, R., “A Distributed Algorithm for ATMS,” UCLA Cognitive Systems Laboratory, Technical Report 880057 (R-109S), March 1988.

(R-108). Dechter, R., and A. Dechter, “Belief Maintenance in Dynamic Constraint Networks,” UCLA Cognitive Systems Laboratory, Technical Report 880056 (R-108-L), March 1988. (R-108-S) in Proceedings, AAAI-88, St. Paul, MN, 37-42, August 1988.

(R-107).[R-107-Shrobe] Pearl, J., “Evidential Reasoning under Uncertainty,” UCLA Cognitive Systems Laboratory, Technical Report 880055 (R-107), February 1988. In H. Shrobe (Ed.), Exploring Artificial Intelligence: Survey Talks from the National Conferences on Artificial Intelligence, Morgan and Kaufmann, 381-418, 1988.
[R-107-AR] Also in Annual Reviews of Computer Science, Vol. 4, 1989 (“Reasoning Under Uncertainty”), 37-72.

(R-106). Pearl, J., “Bayesian and Belief-Functions Formalisms for Evidential Reasoning: A Conceptual Analysis,” UCLA Cognitive Systems Laboratory, Technical Report 880054 (R-106), January 1988. Short version (R-106-S) in Proceedings, 5th Israeli Symposium on Artificial Intelligence, Tel Aviv, 398-424, December 1988. An extended version (R-106-S-II) in Z.W. Ras and M. Zemankova (Eds.), INTELLIGENT SYSTEMS, State of the Art and Future Directions Ellis Horwood Publishers, 73-117, 1990.

(R-105). Pearl, J., “On Probability Intervals,” UCLA Cognitive Systems Laboratory, Technical Report 880094 (R-105), January 1988. In International Journal of Approximate Reasoning, Vol. 2:3, 211-216, July 1988.

(R-103). Verma, T., “Some Mathematical Properties of Dependency Models,” UCLA Cognitive Systems Laboratory, Technical Report (R-103), August 1987.

(R-102). Geiger, D., “Towards the Formalization of Informational Dependencies,” UCLA Cognitive Systems Laboratory, Technical Report 880053 (R-102), (Based on the author’s MS thesis), Dec 3, 1987.

(R-101). Verma, T., & J. Pearl, “Influence Diagrams and d-Separation,” UCLA Cognitive Systems Laboratory, Technical Report 880052 (R-101), March 1988.

(R-100). Pearl, J., “A Probabilistic Treatment of the Yale Shooting Problem,” UCLA Cognitive Systems Laboratory, Technical Report 870068 (R-100), September 1987.

(R-98). Dalkey, N., “A Logic of Information Systems,” UCLA Cognitive Systems Laboratory, Technical Report 870057 (R-98), August 1987, in Proceedings, 6th Workshop on Maximum Entropy and Bayesian Networks, Seattle, WA, August 1987.

(R-97).Geiger, D. & J. Pearl, “Logical and Algorithmic Properties of Conditional Independence,” UCLA Cognitive Systems Laboratory, Technical Report 870056 (R-97), August 1987. A short version (R-97-II-S) in Proceedings, 2nd International Workshop on Artificial Intelligence and Statistics, Miami, FL, (19-1)-(19-10), January 1989.
(R-97-II-L).Geiger, D. & J. Pearl, “Logical and Algorithmic Properties of Conditional Independence,” in The Annals of Statistics, Vol. 21, No. 4, 2001-2021, 1993.

(R-96). Pearl, J., “Deciding Consistency in Inheritance Networks,” UCLA Cognitive Systems Laboratory, Technical Report 870053 (R-96), August 1987.

(R-95). Paz, A., “A Full Characterization of Pseudographoids in Terms of Families of Undirected Graphs,” UCLA Cognitive Systems Laboratory, Technical Report 870055 (R-95), September 1987.

(R-94). Geffner, H., & Pearl, J., “A Framework for Reasoning with Defaults,” UCLA Cognitive Systems Laboratory, Technical Report 870058 (R-94), March 1988. In Knowledge Representation and Defeasible Reasoning, H. Kyburg, R. Loui and G. Carlson (eds), Kluwer Academic Publishers, 1990 (a compilation of papers presented at the Conference on Exact Philosophy, June 1988), 69-87.

(R-93). Pearl, J., “Probabilistic Semantics for a Subset of Default Reasoning,” UCLA Cognitive Systems Laboratory, Technical Report 870052 (R-93), March 1988.

(R-92). Dechter, Rina, & Pearl, J., “Tree-Clustering Schemes for Constraint-Processing,” UCLA Cognitive Systems Laboratory, Technical Report 870065 (R-92), June 1987, in Proceedings, AAAI-88, St. Paul, MN, 150-154, August 1988. Also in Artificial Intelligence, Vol. 38:3, 353-366, April 1989.

(R-91). Pearl, J., “An Inquiry into Computer Understanding,” (Discussion of P. Cheeseman’s paper), UCLA Cognitive Systems Laboratory, Technical Report 870051 (R-91), June 1987.
“On Logic and Probability,” Computational Intelligence, Vol. 4, 90-94, April 1988.

(R-90). Dechter, Rina & Pearl, J., “Network-Based Heuristics for Constraint-Satisfaction Problems,” UCLA Cognitive Systems Laboratory, Technical Report 870037 (R-90), May 1987. In Artificial Intelligence, Vol. 34:1, 1-38, December 1987. Also in L. Kanal and V. Kumar (Eds.), Search in AI, Springer-Verlag, 370-425, 1988.

(R-89). Dalkey, N., “Modeling vs. Inductive Inference for Dealing with Probabilistic Knowledge,” Cognitive Systems Laboratory Technical Report CSD-870050 (R-89), Proceedings, 2nd AAAI Workshop on Uncertainty in Artificial Intelligence , Philadelphia, PA, 63-70, August 1986.

(R-88). Judea Pearl, “Do we Need Higher-Order Probabilities and, If so, What do they Mean?,” UCLA Cognitive Systems Laboratory, Technical Report 870036 (R-88), June 1987, in Proceedings, AAAI Workshop on Uncertainty in AI, Seattle, WA, 47-60, July 1987.

(R-87). Lei Xu & Judea Pearl, “Structuring Causal Tree Models with Continuous Variables,” Department of Automation, Tsinghua University, Beijing, China, and UCLA Cognitive Systems Laboratory, Technical Report 870035 (R-87), June, 1987, in Proceedings, AAAI Workshop on Uncertainty in AI, Seattle, WA, 170-179, July 1987. Also in L.N. Kanal, T.S. Levitt, and J.F. Lemmer (Eds.), Uncertainty in Artificial Intelligence 3, Amsterdam: Elsevier Science Publishers, 209-219, 1989.

(R-86). Dechter, R., & Pearl, J., “The Optimality of A *,” UCLA Cognitive Systems Laboratory, Technical Report 870049 (R-86), August 1987. In L. Kanal and V. Kumar (Eds.), Search in AI, Springer-Verlag, 166-199, 1988.

(R-85). Dalkey, Norman C., “The Inductive Logic of Information Systems,” UCLA Cognitive Systems Laboratory, Technical Report 870034 (R-85), April, 1987, in Proceedings, AAAI Workshop on Uncertainty in AI, Seattle, WA, 205-211, July 1987. Also in L.N. Kanal, T.S. Levitt and J.F. Lemmer (Eds.). Uncertainty in Artificial Intelligence 3, Amsterdam: Elsevier Science Publishers, 375-386, 1989.

(R-84). Geffner, H., & Pearl, J., “On the Probabilistic Semantics of Connectionist Networks,” UCLA Cognitive Systems Laboratory, Technical Report 870033 (R-84), in Proceedings, 1st IEEE International Conference on Neural Networks, San Diego, CA, 187-195, June 1987.

(R-83). Geiger, Daniel, “The Non-Axiomatizability of Dependencies in Directed Acyclic Graphs,” UCLA Cognitive Systems Laboratory, Technical Report 870048 (R-83), June, 1987.

(R-82). Rebane, G., & Pearl, J., “The Recovery of Causal Poly-Trees from Statistical Data,” UCLA Cognitive System Laboratory, Technical Report 870031 (R-82), March, 1987, in Proceedings, AAAI Workshop on Uncertainty in AI, Seattle, WA, 222-228, July 1987. Also in L.N. Kanal, T.S. Levitt, and J.F. Lemmer (Eds.), Uncertainty in Artificial Intelligence 3, Amsterdam: Elsevier Science Publishers, 175-182, 1989.

(R-81). Dechter, A., & Dechter, R., “Removing Redundancies in Constraint Networks,” UCLA Cognitive Systems Laboratory, Technical Report 870006 (R-81), February 1987, in Proceedings, AAAI Conference, Seattle, WA, 105-109, July 1987.

(R-80). Dechter, R., “A Constraint-Network Approach to Truth-Maintenance,” UCLA Cognitive Systems Laboratory, Technical Report 870009 (R-80), February 1987.

(R-79-II). Pearl, J., & Verma,T., “The Logic of Representing Dependencies by Directed Graphs,” UCLA Cognitive Systems Laboratory, Technical Report 870004 (R-79-II), February 1987, in Proceedings, AAAI Conference, Seattle, WA, 374-379, July 1987.

(R-78). Ben-Bassat, M., “Taxonomy, Structure and Implementation of Evidential Reasoning Models,” UCLA Computer Science Department, Technical Report 870005 (R-78); Proceedings, 2nd AAAI Workshop on Uncertainty in AI, Philadelphia, PA, 17-28, August 1986.

(R-77). Dechter, R., “Constraint Processing Incorporating Backjumping, Learning and Cutset-Decomposition,” UCLA Cognitive Systems Laboratory, Technical Report 870010 (R-77), November 1987, in Proceedings, 4th IEEE Conference, San Diego, CA, 312-319, March 1988.
(R-77-II). Dechter, R., “Enhancement Schemes for Constraint Processing: Backjumping, Learning and Cutset Decomposition,” (extended version) in Artificial Intelligence, Vol. 41 (1989/90), 273-312, 1990.

(R-76). Dechter, R., “Decomposing an N-ary Relation into a Tree of Binary Relations,” UCLA Cognitive Systems Laboratory, Technical Report 870011 (R-76), January 1987, in Proceedings, 6th Conference on Principles of Database Systems, San Diego, CA, 185-189, March 1987.
(R-76-II). Dechter, R., “Decomposing a Relation into a Tree of Binary Relations” In Journal of Computer and System Sciences, 41, 2-24, 1990. A Special Issue on the theory of relational databases

(R-75). Pearl, J. & Korf, R., “Search Techniques,” UCLA Cognitive Systems Laboratory, Technical Report (R-75), December 1986, Annual Review of Computer Science, Vol. II, 451-467, 1987.

(R-74). Dechter, A., & Dechter, R., “Minimal Constraint Graphs,” UCLA Cognitive Systems Laboratory, Technical Report 870007 (R-74), December 1986.

(R-73). Geffner, H. & Pearl, J., “An Improved Constraint-Propagation Algorithm for Diagnosis.” UCLA Cognitive Systems Laboratory, Technical Report 870012 (R-73), December 1986, in Proceedings, IJCAI-87 Conference, Milano, Italy, 1105-1111, August 1987.

(R-72). Dechter, R., “Constraint-Directed Approach to Diagnosis,” UCLA Cognitive Systems Laboratory, Technical Report (R-72), September 1988.

(R-71). Pearl, J., “Polya’s `Patterns of Plausible Inference’ and the Quest for Modularity,” UCLA Cognitive Systems Laboratory, Technical Report 870064 (R-71), September 1986.

(R-70). Pearl, J. & Verma, T., “Formal Properties of Probabilistic Dependencies & Their Graphical Representations,” UCLA Computer Science Department Technical Report 860019 (R-70), October 1986.

(R-69). Pearl, J., “Embracing Causality in Default Reasoning,” UCLA Computer Science Department Technical Report 860020 (R-69), September 1986, in Proceedings, AAAI Conference, Seattle, WA, 369-373, July 1987. Also in Artificial Intelligence, Vol. 35:2, 259-271, June 1988.

(R-68). Pearl, J., “Evidential Reasoning Using Stochastic Simulation of Causal Models,” UCLA Computer Science Department, Technical Report 860021 (R-68); Artificial Intelligence, Vol. 32:2, 245-258, 1987.

(R-67). Dechter, R., & Pearl, J., “The Cycle-Cutset Method for Improving Search Performance in AI Applications,” UCLA Computer Science Department, Technical Report 860022 (R-67), in Proceedings, 3rd IEEE Conference on Artificial Intelligence Applications, Orlando, FL, 224-230, February 1987.

(R-66). Geffner, H. & Pearl, J., “A Distributed Approach to Diagnosis,” UCLA Computer Science Department, Technical Report 860023 (R-66); extended version, “A Distributed Diagnosis of Systems with Multiple Faults,” in Proceedings, 3rd IEEE Conference on Artificial Intelligence Applications, Orlando, Florida, 156-162, February 1987.

(R-65). Verma, T. and Pearl. J., “Causal Networks: Semantics and Expressiveness,” UCLA Cognitive Systems Laboratory Technical Report 870032 (R-65), June 1987, in R. Shachter, T.S. Levitt, and L.N. Kanal (Eds.), Uncertainty in Artificial Intelligence 4, Proceedings of the 4th Workshop on Uncertainty in Artificial Intelligence, Elsevier Science Publishers, 69-76, 1990.

(R-64). Pearl, J., “Distributed Revision of Composite Beliefs,” UCLA Cognitive Systems Laboratory, Technical Report 860045 (R-64), Proceedings, 2nd AAAI Workshop on Uncertainty in Artificial Intelligence, Philadelphia, PA, 201-209, August 1986.
(R-64-UAI) in J.F. Lemmer and L.N. Kanal (Eds.), Uncertainty in Artificial Intelligence 2, North-Holland Publishing Co., Amsterdam, 291-316, 1988.
(R-64-AI)Artificial Intelligence, Vol. 33 (2), February 1987, 173-215.

(R-63) (R-63). Roizen, I. & Pearl, J., “Learning Link-Probabilities in Causal Trees,” UCLA Cognitive Systems Laboratory, Technical Report 860095 (R-63), Proceedings, 2nd AAAI Workshop on Uncertainty in Artificial Intelligence, Philadelphia, PA, 211-214, August 1986.

(R-62). Pearl, J., “Jeffrey’s Rule, Passage of Experience, and Neo-Bayesianism,” UCLA Cognitive Systems Laboratory Technical Report 860099 (R-62), May 1986. A later version, June 1989, in H. Kyburg, R. Loui, and G. Carlson (Eds), Knowledge Representation and Defeasible Reasoning, Kluwer Academic Publishers, (a compilation of papers presented at the Conference on Exact Philosophy, June 1988), 245-265, 1990 .

(R-61). Zukerman, I. & Pearl, J., “Comprehension-Driven Generation of Meta-Technical Utterances in Math Tutoring,” UCLA Computer Science Department, Technical Report 860097 (R-61), Proceedings, AAAI-86, Philadelphia, PA, 606-611, August 1986.

(R-60). Zukerman, I., “Computer-Driven Generation of Meta-Technical Utterances in Math Tutoring,” Ph.D. disseration, UCLA Computer Science Department, Technical Report 8600## (R-60), 1986.

(R-59). Pinto, J. A., “Relevance-Based Propagation in Bayesian Networks,” Master’s Thesis, UCLA Computer Science Department, 1986; CSD Technical Report 860098 (R-59).

(R-58). Dechter, R., “Learning While Searching in Constraint-Satisfaction Problems,” UCLA Computer Science Department Technical Report (R-58), Proceedings, AAAI-86, Philadelphia, PA, 178-183, August 1986.

(R-57). Dechter, R. & Dechter, A., “Properties of Greedily Optimized Ordering Problems,” UCLA., Computer Science Department, Technical Report 860048 (R-57); Proceedings, 6th Canadian AI Conference, Montreal, 245-250, May 1986; an extended version (R-57-S) in ORSA Journal of Computing, Vol. 1:3, Summer 1989.

(R-56). Pearl, J. & Paz, A., “On the Logic of Representing Dependencies by Graphs,” UCLA Cognitive Systems Laboratory, Technical Report 860047 (R-56).
In Proceedings, 1986 Canadian AI Conference, Montreal, 94-98, May 1986.

(R-55). Pearl, J., “On the Logic of Probabilistic Dependencies,” UCLA Computer Science Department Technical Report 860062 (R-55); Proceedings, American Association for Artificial Intelligence `86, Philadelphia, PA, 339-343, August 1986.

(R-54). Pearl, J., “Causal Reasoning with Uncertain Continuous Quantities,” UCLA Computer Science Department Technical Report 860051 (R-54), October 1987.

(R-53). Pearl, J. & Paz, A., “GRAPHOIDS: a Graph-Based Logic for Reasoning about Relevance Relations,” UCLA Computer Science Department Technical Report R-53, CSD-850038.
In B. Du Boulay, D. Hogg, and L. Steels (Eds.), Advances in Artificial Intelligence-II, North-Holland Publishing Co., 357-363, 1987.

(R-53-L). Pearl, J. & Paz, A., “GRAPHOIDS: a Graph-Based Logic for Reasoning about Relevance Relations,” UCLA Computer Science Department Technical Report R-53-L.
Long version of R-53 (in B. Du Boulay, D. Hogg, and L. Steels (Eds.), Advances in Artificial Intelligence-II, North-Holland Publishing Co., 357-363, 1987).

(R-52). Dechter, R., “Studies in the Use and Generation of Heuristics,” Ph.D. dissertation, UCLA Computer Science Department, 1985; CSD Technical Report 850033 (R-52).

(R-51). Pearl, J., “On Evidential Reasoning in a Hierarchy of Hypotheses,” UCLA Computer Science Department Technical Report 850032 (R-51); Research Note, Journal of Artificial Intelligence, 28 (1), 9-15, February 1986.

(R-49). Pearl, J., “How to Do with Probabilities What People Say You Can’t,” UCLA Computer Science Department Technical Report 850031 (R-49); Proceedings, 2nd IEEE Conference on AI Applications, Miami, FL, 6-12, December 1985.
Also in Charles L. Wesibin (Ed.), AI Applications, Amsterdam: North-Holland, 6-12, l988.

(R-48). Dechter, R. & Pearl, J., “A Problem Simplification Approach That Generates Heuristics for Constraint-Satisfaction Problems,” UCLA Computer Science Department Technical Report 850014 (R-48). In J.Hayes et al (Eds.), Machine Intelligence, Oxford: Clarendon Press, Vol. 11, 125-156, 1988.

(R-47). Pearl, J. & Tarsi, M., “Structuring Causal Trees,” UCLA Computer Science Department Technical Report 850029 (R-47); Journal of Complexity, Vol. 2 (1) 60-77, March 1986.

(R-46). Pearl, J., “Markov and Bayes Networks: a Comparison of Two Graphical Representations of Probabilistic Knowledge,” UCLA Computer Science Department Technical Report 860024 (R-46), October 1986.

(R-45). Pearl, J., “Bayes Decision Methods,” UCLA Computer Science Department Technical Report 850023 (R-45); Encyclopedia of AI, Wiley Interscience, New York, 48-56. Also in 2nd Edition, 1992, 89-98, 1987 (entitled “Bayesian Inference Methods”).

(R-44). Pearl, J., “A Constraint-Propagation Approach to Probabilistic Reasoning,” UCLA Computer Science Department Technical Report 850020 (R-44); Proceedings, Workshop on Uncertainty and Probability in Artificial Intelligence, UCLA, August 14-16, 31-42, 1985.
In Kanal, L. N. & Lemmer, J. (Eds.), Uncertainty in Artificial Intelligence, North-Holland, Amsterdam, 1986, 357-369.

(R-43). Pearl, J., “Bayesian Networks: a Model of Self-Activated Memory for Evidential Reasoning,” UCLA Computer Science Department Technical Report 850021 (R-43); Proceedings, Cognitive Science Society, UC Irvine, 329-334, August 15-17, 1985.

(R-42). Pearl, J., “Fusion, Propagation and Structuring in Belief Networks,” UCLA Computer Science Department Technical Report 850022 (R-42); Artificial Intelligence, Vol. 29, No. 3, 241-288, September 1986.

(R-41) Dalkey, N. C., “Prior Probabilities Revisited,” UCLA Cognitive Systems Laboratory Technical Report (R-41), presented at the 4th Workshop on Maximum Entropy and Bayesian Methods in Applied Statistics, University of Calgary, August 5-8, 1984.

(R-40) Roizen, I. & Pearl, J., “The Average Performance of Three Game-Searching Algorithms,” UCLA Cognitive Systems Laboratory Technical Report (R-40), July 1983.

(R-39). Zukerman, I. & Pearl, J., “Listener Model for the Generation of Meta-Technical Utterances in Math Tutoring,” UCLA Computer Science Department Technical Report 840064 (R-39), December 1984.

(R-38). Pearl, J., “Learning Hidden Causes From Empirical Data,” UCLA Computer Science Department, Technical Report 840065 (R-38); Proceedings, IJCAI-85, Los Angeles, CA, 567-572, August 1985.

(R-37). Dechter, R. & Pearl, J., “The Anatomy of Easy Problems: a Constraint-Satisfaction Formulation,” UCLA Computer Science Department, Technical Report 840063 (R-37); Proceedings, IJCAI-85, Los Angeles, CA, 1066-1072, August 1985.

(R-36). Tarsi, M. & Pearl, J., “Algorithmic Reconstruction of Trees,” UCLA Computer Science Department Technical Report 840061 (R-36), December 1984.

(R-35) Kim, J. H., “CONVINCE: A CONVersational INference Consolidation Engine,” Ph.D. dissertation, UCLA Computer Science Department; CSD Technical Report 840067 (R-35) March 1984; IEEE Transactions on Systems, Man and Cybernetics, Vol. 17 (2), 120-132, 1987.

(R-34) Michon, G. P., “RECURSIVE RANDOM GAMES: a Probabilistic Model for Perfect Information Games,” Ph.D. dissertation, UCLA Computer Science Department, Technical Report 840029 (R-34), 1983.

(R-27) Dechter, R. & Pearl, J., “The Optimality of A* Revisited,” UCLA-ENG-CSL-83-28 (R-27), 1983; Proceedings, AAAI-83, 95-99, 1983.

(R-25) Kim, J. H. & Pearl, J., “A Computational Model for Combined Causal and Diagnostic Reasoning in Inference Systems,” UCLA-ENG-CSL-83-03 (R-25), January 1983; Rev. I, May 1983; Proceedings, IJCAI-83, 190-193, 1983.

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Pearl, J., “Branching Factor,” Encyclopedia of AI, Wiley Interscience, New York, 81-82, 1987. Also in 2nd Edition, 127-128, 1992.

Pearl, J., “Game Trees,” Encyclopedia of AI, Wiley Interscience, New York, 319-321, 1987. Also in 2nd Edition, 550-552, 1992. (Reprint #50)

Pearl, J., “AND/OR Graphs,” Encyclopedia of AI, Wiley Interscience, New York, 7-8, 1987. Also in 2nd Edition, 28-30, 1992.

Dalkey, N., “Comparison of Minimum Cross-Entropy Inference with Minimally Informative Information Systems.” Presented at the 6th Workshop on Maximum Entropy and Bayesian Methods in Applied Statistics, Seattle, Wash., August 1986.

Dalkey, N., “Inductive Inference and the Representation of Uncertainty.” Presented at the Workshop on Uncertainty and Probability in Artificial Intelligence, UCLA, August 1985. In Kanal & Lemmer (Eds.) Uncertainty in AI, North-Holland Publishing Co., Amsterdam, 1986, 393-397.

Dechter, R. & Kleinrock, L., “Parallel Algorithms for Multi-Processing Broadcast Channels” IEEE Transactions in Computers, Vol. C-35, No. 3, 210-219, 1986.

Dechter, R. & Pearl, J., “Generalized Best-First Search Strategies and the Optimality of A*,” UCLA Computer Science Department Technical Report (Reprint #43). Journal of the Association for Computing Machinery, Vol. 32, No. 3, 505-536, July 1985.

Ben-Bassat, M. & Maler, O., “A Framework for Control Strategies in Uncertain Inference Networks,” Proceedings, Workshop on Uncertainty and Probability in AI, UCLA, Los Angeles, CA, 143-151, August 1985.

Ben-Bassat, M., “Expert Systems for Clinical Diagnosis,” in Gupta et al. (Eds.), Approximate Reasoning in Expert Systems, North-Holland, Amsterdam, the Netherlands, 1985.

Dalkey, N., “Inductive Inference and the Maximum Entropy Principle,” in C. Ray Smith and W.T. Grandy (Eds.), Maximum Entropy and Bayesian Methods in Inverse Problems, D. Reidel, 1985.

Pearl, J., Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addison-Wesley, Reading, MA., 1984.

Pearl, J., “Some Recent Results in Heuristic Search Theory,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-6, No. 1, 1-13, January 1984.

Pearl, J. (Ed.), Search and Heuristics, North-Holland Publishing Co., Amsterdam, 1983.

Dalkey, N., “Information Pooling as the Composition of Inquiry Systems.” Presented at the Conference on Information Pooling and Group Decision, Irvine, CA, March 1983.

Pearl, J., “Knowledge versus Search: a Quantitative Analysis Using A*,” Artificial Intelligence, 20(1):1-13, January 1983a.

Roizen, I. & Pearl, J., “A Minimax Algorithm Better than Alpha-Beta?: Yes and No,” Artificial Intelligence, 21(1-2):199-200, March 1983.

Karp, R. M. & Pearl, J., “Searching for an Optimal Path in a Tree with Random Costs,” Artificial Intelligence, 21(1-2):99-116, March 1983. (Reprint #38)

Pearl, J., “On the Discovery and Generation of Certain Heuristics,” AI Magazine, Winter/Spring, 23-33, 1983b. (Reprint #39) Also in Readings from AI Magazine, R. Engelmore (ed), Menlo Park: AAAI Press, 58-66, 1988.

Pearl, J., “Test Tubes versus Fruit Flies in the Design of Gothic Cathedrals,” AI Journal, preface, Special Issue on “Search and Heuristics” in memory of John Gaschnig, 21:1-6, 1983c.

Pearl, J., “On the Nature of Pathology in Game Searching,” Artificial Intelligence, 20, 427-453, 1983d.

Pearl, J., “Game-Searching Theory: Survey of Recent Results” in M. Bramer (Ed.), Computer Game-Playing: Theory and Practice, Halsted Press, Chapter 20, 276-284, 1983.

(R-28) Pearl, J., Leal, A. & Saleh, J., “GODDESS: a Goal-Directed Decision Structuring System,” IEEE Trans. on Pattern Recognition and Machine Intelligence, 4(3):250-262, May 1982.

(R-29) Pearl, J. & Kim, J. H., “Studies in Semi-Admissible Heuristics,” IEEE Trans. on Pattern Recognition and Machine Intelligence, 4(4):392-399, July 1982.

(R-30) Pearl, J., “Reverend Bayes on Inference Engines: A Distributed Hierarchical Approach,” Proceedings, AAAI National Conference on AI, Pittsburgh, PA, 133-136, August 1982a.

Pearl, J., “The Solution for the Branching Factor of the Alpha-Beta Pruning Algorithm and Its Optimality,” CACM, 25(8):559-564, August 1982b.

Dalkey, N., “Min-Score Inference on Probability Systems,” UCLA-ENG-CSL-8112, June, 1981.

(R-24) Pearl, J., “A Space-Efficient On-Line Method of Computing Quantile Estimates,” Journal of Algorithms, 2(2):164-177, June 1981a.

(R-26) Burns, M. & Pearl, J., “Causal and Diagnostic Inferences: A Comparison of Validity,” Organizational Behavior and Human Performance, 28:379-394, 1981.

1976-1980

Dalkey, N., “The Aggregation of Probability Estimates,” UCLA-ENG-CSL-8025, August 1980.

(R-20) Pearl, J., “SCOUT: A Simple Game-Searching Algorithm with Proven Optimal Properties,” Proceedings, 1st Annual National Conference on Artificial Intelligence, Stanford University, 143-145, August 1980a.

(R-21) Pearl, J., “Asymptotic Properties of Minimax Trees and Game-Searching Procedures,” Artificial Intelligence, 14(2):113-138, September 1980b.

(R-22) Pearl, J. & Crolotte, A., “Storage Space versus Validity of Answers in Probabilistic Question-Answering Systems,” IEEE Trans. on Information Theory, IT-26(6):633-640, November 1980.

(R-23) Huyn, N., Dechter, R. & Pearl, J., “Probabilistic Analysis of the Complexity of A*,” Artificial Intelligence, 15(3):241-254, December 1980.

Pearl, J., “On the Connection Between the Complexity and Credibility of Inferred Models,” International Journal of General Systems, 4: 255–264, 1978.

Pearl, J., “A Framework for Processing Value Judgments,” IEEE Transactions on Systems, Man, and Cybernetics, 7(5): 349–354, 1977.

Pearl, J., “Theoretical Bounds on the Complexity of Inexact Computations,” IEEE Trans. on Information Theory, IT-22(5):580-586, September 1976d.

Selected pre-1975 papers by J. PearlPearl, J., “The Mystery of Problem Representations,” A Tutorial Introduction to a Young Area of Research, University of California Los Angeles, School of Engineering and Applied Science,March 1972.

Pearl, J., “Distinctive properties of quantized vortices in superconducting films,” In J.G. Daunt, D.O. Edwards, F.J. Milford, and M. Yaqub (Eds.), Low Tembperature Physics LT9 (Proceedings of the IXth International Conference on Low Temperature Physics), NY: Plenum Press, 1965.

Pearl, J., “Vortexes are creating a stir in the superconductor field,” Electronics, pp. 100-105, June 13, 1966.

Return to Pearl’s HomePage

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REPORT REQUESTS are to be directed to:

 

Prof. Judea Pearl ([email protected]) UCLA Computer Science Department 4532 Boelter Hall Los Angeles, California 90024-1596 (310) 825-3243

References

1. http://bayes.cs.ucla.edu/csl_papers.html