The following are the published books and papers by David Poole, by year.

2023

2022

  • Matthew Dirks and David Poole, "Automatic Neural Network Hyperparameter Optimization for Extrapolation: Lessons Learned from Visible and Near-Infrared Spectroscopy of Mango Fruit", Chemometrics and Intelligent Laboratory Systems Volume 231, DOI: 10.1016/j.chemolab.2022.104685
  • David Poole and Frank Wood, "Probabilistic Programming Languages: Independent Choices and Deterministic Systems", in Geffner, H., Dechter, R., and Halpern, J.Y. (eds.) Probabilistic and Causal Inference: The Works of Judea Pearl, ACM Books 2022, pp. 691-712

2021

  • Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting and Sriraam Natarajan Structure learning for relational logistic regression: an ensemble approach Data Mining and Knowledge Discovery (2021). https://doi.org/10.1007/s10618-021-00770-8.
  • Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole Knowledge Hypergraph Embedding Meets Relational Algebra. arXiv:2102.09557 [cs.LG]
  • Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, and David Poole Introduction to Lifted Inference, MIT Press, 2021. Including the following chapters:
    • Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, and David Poole, ``Statistical Relational AI: Representation, Inference and Learning''
    • Angelika Kimmig and David Poole ``Modeling and Reasoning with Statistical Relational Representations''
    • Seyed Mehran Kazemi, Guy Van den Broeck, and David Poole ``Search-Based Exact Lifted Inference''
    • Wannes Meert, Jaesik Choi, Jacek Kisynski, Hung Bui, Guy Van den Broeck, Adnan Darwiche, Rodrigo de Salvo Braz, and David Poole, ``Lifted Aggregation and Skolemization for Directed Models''
    • Seyed Mehran Kazemi, Guy Van den Broeck, and David Poole, ``First-order Knowledge Compilation''
    • Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, and David Poole ``Domain Liftability''

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

  • Rita Sharma and David Poole, Symmetric Collaborative Filtering using the Noisy Sensor Model in Proc. UAI-2001, Seattle, 2001
  • D. Poole, ``Logical Argumentation, Abduction and Bayesian Decision Theory: A Bayesian Approach to Logical Arguments and its Application to Legal Evidential Reasoning'', Cardozo Law Review, 22 (5-6), October 2001. Reprinted in Tillers and MacCrimmon (Ed.) Dynamics of Judicial Proof: Computation, Logic, and Common Sense Springer-Verlag, 2002.

2000

1999

1998

1997

1996

1995

1994

  • Ramon Lopez de Mantaras and David Poole (Eds), Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI-94),Morgan Kaufmann, 1994.
  • David Poole, ``Representing Diagnosis Knowledge'', Annals of Mathematics and Artificial Intelligence, 11, 33-50, 1994.
  • Nevin Lianwen Zhang, R. Qi and David Poole, ``A Computational Theory of Decision Networks'', International Journal of Approximate Reasoning, 11(2), 83-158, 1994.
  • Nevin Lianwen Zhang and David Poole, ``Intercausal independence and heterogeneous factorization'', Proceedings of the Tenth Conference on Uncertainty in AI (UAI-94), Seattle, July 1994, 606-614.
  • Runping Qi, Nevin Lianwen Zhang and David Poole, ``Solving Asymmetric Decision Problems with Influence Diagrams'', Proceedings of the Tenth Conference on Uncertainty in AI (UAI-94), Seattle, July 1994, 491-497.
  • Nevin Lianwen Zhang and David Poole, ``A simple approach to Bayesian network computations'', Proceedings of the Tenth Biennial Canadian Artificial Intelligence Conference (AI-94), Banff, May 1994, 171-178.
  • David Poole, ``Default Logic'', in D. M. Gabbay, C. J. Hogger J. A. Robinson (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 3, Oxford University Press, 1994, 189-215.
  • David Poole and K. Kanazawa, ``A decision-theoretic abductive basis for planning'', Proc. AAAI Spring Symposium on Decision-Theoretic Planning, Stanford University, March 1994, 232-239.

1993

  • David Poole, ``Probabilistic Horn abduction and Bayesian networks'', Artificial Intelligence, 64(1), 81-129, 1993.
  • Yang Xiang, David Poole and M. P. Beddoes, ``Multiply sectioned Bayesian networks and junction forests for large knowledge-based systems'', Computational Intelligence 9(2), 171-220, May 1993.
  • Yang Xiang, B. Pant, A. Eisen, M. P. Beddoes and David Poole, ``Multiply Sectioned Bayesian Networks for Neuromuscular Diagnosis'', Artificial Intelligence in Medicine, 5(4) 293-314, 1993.
  • David Poole, ``Logic Programming, Abduction and Probability: a top-down anytime algorithm for estimating prior and posterior probabilities'', New Generation Computing, 11(3-4), 377-400, 1993.
  • David Poole, ``Probabilistic Conflicts'', Fourth International Workshop on the Principles of Diagnosis, pp. 178-186, Aberystwyth, Wales, September 1993.
  • David Poole, ``Average-case analysis of a search algorithm for estimating prior and posterior probabilities in Bayesian networks with extreme probabilities'', Proc. Thirteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 606-612, France, August 1993.
  • Andrew Csinger and David Poole, ``Hypothetically Speaking: Default Reasoning and Discourse Structure'', Proc. Thirteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 1179-1184, France, August 1993.
  • David Poole, ``The Use of Conflicts in Searching Bayesian Networks'', Proceedings of the Ninth Conference on Uncertainty in AI (UAI-93), Washington D.C., pages 359-367, July 1993.
  • N.L. Zhang, R. Qi and David Poole, ``Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams'', Proceedings of the Ninth Conference on Uncertainty in AI (UAI-93), Washington D.C., pages 400-407, July 1993.
  • N.L. Zhang, R. Qi and David Poole, ``Minimizing Decision Table Sizes in Stepwise-decomposable Influence Diagrams'', Proc. Fourth International Workshop on Artificial Intelligence and Statistics, Ft. Lauderdale, Florida, pages 423-432, January 1993.

1992

  • David Poole, ``Efficient Model-based Diagnosis: Searching in Bayesian Networks'', Proceedings of the Third International Workshop on Principles of Diagnosis, Rosario, Washington, October 1992.
  • N.L. Zhang and David Poole, ``Stepwise-Decomposable Influence Diagrams'', Proceedings of the Third International Conference on the Principles of Knowledge Representation and Reasoning (KR-1992), Cambridge, Mass., pages 141-152, October 1992.
  • R. Qi and David Poole, ``Two Algorithms for Decision Tree Search'', Proceedings of the Second Pacific Rim International Conference on Artificial Intelligence, Seoul, Korea, pages 121-127, September 1992.
  • R. Qi and David Poole, ``A Framework for U-graph Based Path Planning'', Proceedings of the Second Pacific Rim International Conference on Artificial Intelligence, Seoul, Korea, pages 287-293, September 1992.
  • Y. Xiang, David Poole and M. P. Beddoes, ``Exploring Locality in Bayesian Networks for Large Expert Systems'', Proceedings of the Eighth Conference on Uncertainty in AI (UAI-92), pages 344-351, Stanford, July 1992.
  • L. Zhang and David Poole, ``Sidestepping the Triangulation Problem in Bayesian Net Computation'', Proceedings of the Eighth Conference on Uncertainty in AI (UAI-92), pages 360-367, Stanford, July 1992.
  • David Poole, ``Logic Programming, Abduction and Probability'', Proceedings of the International Conference on Fifth Generation Computer Systems (FGCS'92), pages 530-538, Tokyo, June 1992.
  • David Poole, ``Decision-theoretic Defaults'', Proceedings of the Ninth Biennial Canadian Artificial Intelligence Conference (CSCSI-92), pages 190-197, Vancouver, May 1992.

1991

  • David Poole, ``The effect of knowledge on belief: conditioning, specificity and the lottery paradox in default reasoning'', Artificial Intelligence, 49, 281-307, 1991. Republished in R. J. Brachman, H. J. Levesque and R. Reiter (Eds.), Knowledge Representation, MIT Press, 1991.
  • David Poole, ``Compiling a default reasoning system into Prolog'', New Generation Computing, 9(1), 3-38, 1991.
  • Y. Xiang, B. Pant, A. Eisen, M.P.Beddoes, David Poole, ``PAINULIM: A Neuromuscular Diagnostic Aid Using Multiply Sectioned Bayesian Networks'', Proc. of the ISMM International Conference on Mini and Microcomputers in Medicine and Healthcare, Long Beach, CA, Dec. 1991, pp. 64-69.
  • David Poole and G. Provan, ``Use and Granularity in Consistency-based Diagnosis'', Proc. Second International Workshop on the Principles of Diagnosis, Milan, October 1991, pp. 1-10.
  • David Poole, ``Representing Diagnostic Knowledge for Probabilistic Horn Abduction'', Proc. Twelfth International Joint Conference on Artificial Intelligence (IJCAI), Sydney, Australia, August 1991, pp. 1129-1135. Reprinted in W. Hamscher, L. Console and J. de Kleer (Eds.), Readings in Model-based Diagnosis, Morgan Kaufmann,, 1992.
  • N. Helft, K. Inoue and David Poole, ``Answer Extraction in Circumscription'', Proc. Twelfth International Joint Conference on Artificial Intelligence (IJCAI), Sydney, Australia, August 1991, pp. 426-431.
  • David Poole, ``Representing Bayesian Networks within Probabilistic Horn Abduction'', Proceedings of the Seventh Conference on Uncertainty in AI (UAI-91), Los Angeles, July 1991, pp. 271-278.
  • R. Qi and David Poole, ``Path Planning under Uncertainty'', Proceedings of the Seventh Conference on Uncertainty in AI (UAI-91), Los Angeles, July 1991, pp. 287-294.
  • G. Provan and David Poole, ``The Utility of Consistency-Based Diagnostic Techniques'', Proc. Second International Conference on Principles of Knowledge Representation and Reasoning (KR-1991), Cambridge, Mass., April 1991, pp. 461-472.

1990

  • David Poole, ``A methodology for using a default and abductive reasoning system'', International Journal of Intelligent Systems, 1990, 5(5), 521-548, 1990.
  • David Poole and G. Provan, ``What is an optimal diagnosis?'', Proceedings of the Sixth Conference on Uncertainty in AI (UAI-90), Boston, July 1990, pp. 46-53. Revised version published as ``What is the Most Likely Diagnosis?'', in P. P. Bonissone, M. Henrion, L. N. Kanal and J. Lemmer (Eds.) Uncertainty in Artificial Intelligence VI, Elsevier, North Holland, 1991.
  • M. Horsch and David Poole, ``A dynamic approach to probabilistic inference using Bayesian networks'', Proceedings of the Sixth Conference on Uncertainty in AI (UAI-90), Boston, July 1990, pp. 155-161.
  • David Poole, ``Dialectics and Specificity: Conditioning in Logic-based hypothetical reasoning'',Proceedings of the Eighth Biennial Conference of the Canadian Society for Computational Studies of Intelligence (CSCSI-90), Ottawa, May 1990, pp. 69-76. () Revised version in Proceedings of the Third International Workshop on Nonmonotonic Reasoning, California, June 1990, pp. 201-208.
  • Y. Xiang, M. P. Beddoes and David Poole, ``Sequential Updating of conditional probability in Bayesian networks by posterior probability'' Proceedings of the Eighth Biennial Conference of the Canadian Society for Computational Studies of Intelligence (CSCSI-90), Ottawa, May 1990, pp. 21-27.
  • David Poole, ``Formal Logic'', in Standards and Review Manual for Certification in Knowledge Engineering, Handbook of Theory and Practice, International Association for Knowledge Engineers, Systemsware Corporation (Publisher), July 1990.
  • David Poole, ``Hypo-deductive reasoning for abduction, default reasoning and design'', Proc. AAAI Spring Symposium on Automated Abduction, Stanford University, March 1990.
  • N. Helft, K. Inoue and David Poole, ``Extracting answers in circumscription'', ICOT Technical Memorandum TM-855, ICOT, 1989. Also in First Workshop on Defeasible Reasoning and Uncertainty Management Systems, Marseille, February, 1990.

1989

  • David Poole, ``Explanation and Prediction: An Architecture for Default and Abductive Reasoning'',Computational Intelligence 5(2), 97-110, 1989.
  • A. Csinger and David Poole, ``From Utterance to Belief via Presupposition: Default Reasoning in User-Modelling'', Proc. Conference on Knowledge Based Computer Systems -- KBCS-89, 408-419, Bombay, India, December 1989. Reprinted in S. Ramani, R. Chandrasekar and K. S. R. Anjaneyulu (Eds.) Knowledge Based Computer systems, Lecture Notes in AI, Volume 444, Springer Verlag, 1989.
  • D. L. Poole, ``Normality and Faults in Logic-Based Diagnosis'', Proceedings Eleventh International Joint Conference on Artificial Intelligence (IJCAI), Detroit, August 1989, pp. 1304-1310. Reprinted in W. Hamscher, L. Console and J. de Kleer (Eds.), Readings in Model-based Diagnosis, Morgan Kaufmann, forthcoming, 1992.
  • Y. Xiang, M. P. Beddoes and David Poole, ``Can uncertainty management be realized in a finite totally ordered probability algebra?'', Fifth Workshop on Uncertainty in Artificial Intelligence (UAI-89), Windsor Ontario, August 1989, pp. 385-393. Revised version in Uncertainty in Artificial Intelligence: Volume V, M. Henrion, R. Shacter, L. N. Kanal and J. Lemmer (Eds), Elsevier, North-Holland, 41-57, 1990.
  • D. L. Poole, ``What the Lottery Paradox tells us about default reasoning'', Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning (KR-1989), Toronto, May 1989, pp. 333-340.
  • David Poole, ``Minimalist AI and the Theorist conjecture'', AAAI Workshop on Defeasible Reasoning with Specificity and Multiple Inheritance, St. Louis, April 1989.

1988

  • David Poole, ``A Logical Framework for Default Reasoning'', Artificial Intelligence, 36(1), 27-47, 1988.
  • D. L. Poole, ``Representing Knowledge for Logic-based Diagnosis'', Proc. International Conference on Fifth Generation Computer Systems 1988, Tokyo, November 1988, pp. 1282-1290.
  • E. M. Neufeld and D. L. Poole, ``Probabilistic Semantics and Defaults'', Proceedings of the Fourth Workshop Uncertainty in Artificial Intelligence (UAI-88), University of Minnesota, August 1988, pp. 275-282. Revised version as E. M. Neufeld, David Poole and R. Aleliunas, ``Probabilistic Semantics and Defaults'', in R. Shacter et. al. (eds.) Uncertainty in Artificial Intelligence, IV, North Holland, 121-131, 1990.
  • E. M. Neufeld and David Poole, ``Combining Logic and Probability'', peer commentary on P. Cheeseman, ``Inquiry into Computer Understanding'' (Edited by M. McLeish), Computational Intelligence, 4(1), 98-99. 1988.
  • D. L. Poole and E.M.Neufeld, ``Sound Probabilistic Inference in Prolog: An executable specification of influence graphs'', invited paper, Proc. First International Symposium on Artificial Intelligence, Monterrey, Mexico, pp. 37-54, October 1988.

1987

  • D. L. Poole, ``Variables in Hypotheses'', Proceedings Tenth International Joint Conference on Artificial Intelligence (IJCAI), Milano, August 1987, pp. 905-908. (scan)
  • E. M. Neufeld and D. L. Poole, ``Towards solving the multiple extension problem: combining defaults and probabilities'', Proceedings Third AAAI Workshop on Reasoning with Uncertainty (UAI), Seattle, July 1987, pp. 305-312. Revised version in Uncertainty in Artificial Intelligence, III, North Holland, 1989.
  • D. L. Poole, R. Goebel and R. Aleliunas, ``Theorist : a logical reasoning system for defaults and diagnosis'', in N. Cercone and G. McCalla (Eds.) The Knowledge Frontier: Essays in the Representation of Knowledge, Springer Varlag, New York, 1987, pp. 331-352.
  • David Poole, ``The Use of Logic'', peer commentary on D. McDermott, ``Taking Issues: A Critique of Pure Reason'', (Edited by H. Levesque), Computational Intelligence, 3(3), 205-206, 1987.

1986

  • D. L. Poole and R. G. Goebel, ``Gracefully Adding Negation and Disjunction to Prolog'', Proc. Third International Logic Programming Conference, Springer-Verlag Lecture Notes in Computer Science 225, pp. 635-641, 1986.
  • R. Goebel, K. Furukawa and D. L. Poole, ``Using Definite Clauses and Integrity Constraints as the Basis for a Theory Formation Approach to Diagnostic Reasoning'', Proc. Third International Logic Programming Conference, Springer-Verlag Lecture Notes in Computer Science 225, pp. 211-222, 1986.

1985

  • D. L. Poole, `` On the Comparison of Theories: Preferring the Most Specific Explanation'', Proceedings Ninth International Joint Conference on Artificial Intelligence (IJCAI), Los Angeles, August 1985, pp. 144-147. (a scan)
  • M. L. Jones and D. L. Poole, ``An Expert System for Educational Diagnosis Based on Default Logic'', Proc. Fifth International Workshop on Expert Systems and Applications, Avignon, France, May 1985, pp. 673-683.
  • D. L. Poole and R. G. Goebel, ``On Eliminating loops in Prolog'', SIGPLAN Notices, Vol 20, No 8, August 1985, pp. 38-40,

1984

  • D. L. Poole, ``A Logical System for Default Reasoning'', Proc. AAAI Workshop on Non-Monotonic Reasoning, NY Oct 1984, pp. 373-384.
  • D. L. Poole, ``Making `Clausal' Theorem Provers `Non-Clausal' '', Proc. Canadian Society for Computational Studies of Intelligence National Conference (CSCSI-84), London, May 1984, pp. 124-125.

1980

  • D. L. Poole, ``A Taxonomy of Control in Production Systems'', Proc. Australian Computer Science Conference, Canberra, Jan 1980.
Last updated 2016-02-29 - David Poole, poole@cs.ubc.ca