Papers by David Poole

Journals

• Rita Sharma, David Poole and Clinton Smyth, A Framework for Ontologically-Grounded Probabilistic Matching, to appear International Journal of Approximate Reasoning.
• David Poole, Clinton Smyth and Rita Sharma, Ontology Design for Scientific Theories That Make Probabilistic Predictions, IEEE Intelligent Systems, Special Issue on Semantic Scientific Knowledge Integration - Jan/Feb 2009, pages 27-36
• Saleema Amershi, Giuseppe Carenini, Cristina Conati, Alan K. Mackworth and David Poole, Pedagogy and Usability in Interactive Algorithm Visualizations Designing and Evaluating CIspace, Interacting with Computers, Volume 20, Issue 1, January 2008, Pages 64-96.
• Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger Hoos, and David Poole "CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements", Journal of AI Research, Volume 21, pages 135-191, 2004.
• Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger Hoos, and David Poole, Preference-Based Constrained Optimization with CP-nets,Computational Intelligence, 20(2), Special Issue on Preferencesin Artificial Intelligence and Constraint Processing, 137-157, May 2004. Postscript version.
• Nando de Freitas, Richard Dearden, Frank Hutter, Ruben Morales-Menendez, Jim Mutch and David Poole. Diagnosis by a waiter and a Mars explorer. Invited paper for Proceedings of the IEEE, special issue on sequential state estimation,  94(3), 455-468, March 2004..
• David Poole and Nevin Lianwen Zhang, ``Exploiting contextual independence in probabilistic inference'', Journal of Artificial Intelligence Research,18, 263-313, 2003.
• David Poole, ``Abducing Through Negation as Failure: Stable models within the independent choice logic '' Journal of Logic Programming, Vol 44, Pages 5-35, 2000.
• David Poole, ``Decision Theory, the Situation Calculus and Conditional Plans'', Linköping Electronic Articles in Computer and Information Science, Vol 3 (1998):nr 8. http://www.ep.liu.se/ea/cis/1998/008/ June 15, 1998. The Electronic Transactions on Artificial Intelligence.
• David Poole, ``The Independent Choice Logic for modelling multiple agents under uncertainty'',Artificial Intelligence, 94(1-2), special issue on economic principles of multi-agent systems, pages 7-56, 1997.
• David Poole, ``Probabilistic conflicts in a search algorithm for estimating posterior probabilities in Bayesian networks'', Artificial Intelligence, 88, 69-100, 1996.
• Nevin Lianwen Zhang and David Poole, ``Exploiting Causal Independence in Bayesian Network Inference'', Journal of Artificial Intelligence Research, 5, 301-328, 1996.
• Runping Qi and David Poole, ``A New Method for Influence Diagram Evaluation'', Computational Intelligence, 11(3), 498-528, 1995.
• Andrew Csinger, Kelly S. Booth, David Poole, ``AI Meets Authoring: User Models for Intelligent Multimedia'', Artificial Intelligence Review, special issue on user modelling, 8, 447-468, 1995.
• 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.
• 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, ``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.
• 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, ``Explanation and Prediction: An Architecture for Default and Abductive Reasoning'',Computational Intelligence 5(2), 97-110, 1989.
• David Poole, ``A Logical Framework for Default Reasoning'', Artificial Intelligence, 36(1), 27-47, 1988.

Conference Proceedings

• Jacek Kisynski and David Poole, Lifted Aggregation in Directed First-order Probabilistic Models, Proc. IJCAI 2009.
• Brian Knoll, Jacek Kisynski, Giuseppe Carenini, Cristina Conati, Alan Mackworth and David Poole, "AIspace: Interactive Tools for Learning Artificial Intelligence". In Proceedings of the AAAI 2008 AI Education Colloquium. July 2008.
• David Poole, Clinton Smyth and Rita Sharma, Semantic Science and Machine-Accessible Scientific Theories, AAAI Spring Symposium on Semantic Science Knowledge Integration, Stanford, March 2008.
• David Poole, "Logical Generative Models for Probabilistic Reasoning about Existence, Roles and Identity", 22nd AAAI Conference on AI (AAAI-07), July 2007.
• Mark Crowley, Brent Boerlage and David Poole, ``Adding Local Constraints to Bayesian Networks'', 20th Canadian Conference on Artificial Intelligence, May 2007.
• David Poole and Alan Mackworth, ``Dimensions of Complexity of Intelligent Agents'', International Symposium on Practical Cognitive Agents and Robots, Perth, November 2006.
• Rita Sharma and David Poole, ``Probabilistic  Reasoning with Hierarchically Structured Variables'', Proc. Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05), Edinburgh, August 2005.
• Peter Carbonetto, Jacek Kisynski, Nando de Freitas and David Poole. ``Nonparametric Bayesian Logic'', Proc. 21st Conference on Uncertainty in Artificial Intelligence (UAI 2005), Edinburgh July 2005.
• David Poole and Clinton Smyth, ``Type Uncertainty in Ontologically-Grounded Qualitative Probabilistic Matching'', Eighth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU-2005), Barcelona, July 2005.
• Saleema Amershi, Nicole Arksey, Giuseppe Carenini, Cristina Conati, Alan Mackworth, Heather Maclaren, and David Poole, ``Designing CIspace: Pedagogy and Usability in a Learning Environment for AI'', Tenth Annual Conference on Innovation and Technology in Computer Science Education, Lisbon, Portugal, June 27-29, 2005.
• Rita Sharma and David Poole, ``Probability and Equality: A Probabilistic Model of Identity Uncertainty'', Eighteenth Canadian Conference on Artificial Intellegence, Victoria, May 2005.
• Clinton Smyth and David Poole, Qualitative Probabilistic Matching with Hierarchical Descriptions, KR-2004, June 2004.
• David Poole, First-order probabilistic inference, Proc, IJCAI-03, Acapulco, August 2003,  pp. 985-991.
  
• Rita Sharma and David Poole, Efficient Inference in Large Discrete Domains in UAI-2003, Acapulco, August 2003, pp. 535-542.
• Ruben Morales-Menendez, Nando de Freitas, and David Poole, Estimation and control of industrial processes with particle filters, American Control Conference, Denver Colorado, June 2003.
  
• Giuseppe Carenini, Jocelyn Smith and David Poole, Towards more Conversational and Collaborative
  Recommender Systems, Proc. 2003 International Conference of Intelligent User Interfaces (IUI-2003), Miami, January 2003.
  
• Ruben Morales-Menendez, Nando de Freitas, and David Poole, Real-time monitoring of complex industrial processes with particle filters, Proc. Neural Information Processing Systems (NIPS), Vancouver, December 2002.
• Rita Sharma and David Poole, Symmetric Collaborative Filtering using the Noisy Sensor Model  in Proc. UAI-2001, Seattle, 2001
• David Poole, ``Logic, Knowledge Representation and Bayesian Decision Theory, Invited paper, First International Conference on Computational Logic (CL2000), London, July 2000.
• Peter Gorniak and David Poole, Predicting Future User Actions by Observing Unmodified Applications, Seventeenth National Conference on Artificial Intelligence (AAAI-2000), August 2000.
• Peter Gorniak and David Poole, Building a Stochastic Dynamic Model of Application Use, roc. Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), July 2000.
• Nevin Lianwen Zhang and David Poole, On the role of context-specific independence in Probabilistic Reasoning , Proc. Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, pages 1288--1293, August 1999.
• Craig Boutilier, Ronen Brafman, Holger Hoos, and David Poole, ``Reasoning With Conditional Ceteris Paribus Preference Statements'', in Proc. Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, Sweden 1999.
• Michael C. Horsch and David Poole, ``Estimating the Value of Computation in Flexible Information Refinement'', in Proc. Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI-99), Stockholm, Sweden 1999.
• David Poole, ``Context-specific approximation in probabilistic inference'', Proc. Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), Madison, Wisconsin, pages 447-454, July 1998.
• Michael C. Horsch and David Poole, ``An Anytime Algorithm for Decision Making under Uncertainty'', Proc. Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), Madison, Wisconsin, pages 246-255, July 1998.
• David Poole, ``Probabilistic Partial Evaluation: Exploiting rule structure in probabilistic inference'',Proc. Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), Nagoya, Japan, August 1997, pp. 1284-1291.
• David Poole, ``Multi-agent actions under uncertainty: situation caclulus, discrete time, plans and policies'', IJCAI-97 Workshop on Nonmonotonic Reasoning, Action, and Change, Nagoya, Japan, August 1997, pp. 139-158.
• Andrew Csinger and David Poole, ``Adapting Decision Theory for Multimedia Presentation Design: User Modelling for Intent-based Authoring'', Proc. Twelfth European Conference on Artificial Intelligence (ECAI-96), Budapest, August 1996.
• Craig Boutilier and David Poole, ``Computing Optimal Policies for Partially Observable Decision Processes using Compact Representations'', Proc. Thirteenth National Conference on Artificial Intelligence (AAAI-96), Portland, Oregon, August 1996.
• David Poole, ``A Framework for Decision-Theoretic Planning I: Combining the Situation Calculus, Conditional Plans, Probability and Utility'', Proc. Twelfth Conference on Uncertainty in Artificial Intelligence, Portland, Oregon, August 1996.
• Michael Horsch and David Poole, "Flexible Policy Construction by Information Refinement", Proc. Twelfth Conference on Uncertainty in Artificial Intelligence, Portland Oregon, August 1996.
• Andrew Csinger and David Poole, ``User Models and Perceptual Salience: Formal Abduction for Model Recognition and Presentation Design'', Proc. Fifth International Conference on User Modeling, Kona, HI, 51-58, 1996.
• David Poole, ``Logic Programming for Robot Control'', Proc. Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), Montreal, August 1995, 150-157.
• David Poole, ``Exploiting the Rule Structure for Decision Making within the Independent Choice Logic'', Proceedings of the Eleventh Conference on Uncertainty in AI, Montreal, August 1995, 454-463.
• Nevin Lianwen Zhang and David Poole, ``Intercausal independence and heterogeneous factorization'', Proceedings of the Tenth Conference on Uncertainty in AI, 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, 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, ``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, 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, 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, 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, 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.
• 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, 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, 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, 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.
• 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, 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, forthcoming, 1992.
• N. Helft, K. Inoue and David Poole, ``Answer Extraction in Circumscription'', Proc. Twelfth International Joint Conference on Artificial Intelligence, 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, 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, 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, Cambridge, Mass., April 1991, pp. 461-472.
• David Poole and G. Provan, ``What is an optimal diagnosis?'', Proceedings of the Sixth Conference on Uncertainty in AI, 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, 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.
• 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, 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, 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, Toronto, May 1989, pp. 333-340.
• 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, 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.
• D. L. Poole, ``Variables in Hypotheses'', Proceedings Tenth International Joint Conference on Artificial Intelligence, Milano, August 1987, pp. 905-908.
• 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, Seattle, July 1987, pp. 305-312. Revised version in Uncertainty in Artificial Intelligence, III, North Holland, 1989.
• 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.
• D. L. Poole, ``On the Comparison of Theories: Preferring the Most Specific Explanation'', Proceedings Ninth International Joint Conference on Artificial Intelligence, Los Angeles, August 1985, pp. 144-147.
• D. L. Poole, ``A Logical System for Default Reasoning'', Proc. AAAI Workshop on Non-Monotonic Reasoning, NY Oct 1984, pp. 373-384.
• 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, ``Making `Clausal' Theorem Provers `Non-Clausal' '', Proc. Canadian Society for Computational Studies of Intelligence National Conference (CSCSI-84), London, May 1984, pp. 124-125.
• D. L. Poole, ``A Taxonomy of Control in Production Systems'', Proc. Australian Computer Science Conference, Canberra, Jan 1980.

Books

• David Poole, Alan Mackworth, and Randy Goebel, Computational Intelligence: A Logical Approach, Oxford University Press, 1998.
• Ramon Lopez de Mantaras and David Poole (Eds), Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence,Morgan Kaufmann, 1994.

Book Chapters

• David Poole, Clinton Smyth, Rita Sharma "Semantic Science: Ontologies, Data and Probabilistic Theories" in Paulo C.G. da Costa, Claudia d'Amato, Nicola Fanizzi, Kathryn B. Laskey, Ken Laskey, Thomas Lukasiewicz, Matthias Nickles, and Mike Pool (Eds.), Uncertainty Reasoning for the Semantic Web I, Springer LNAI/LNCS, 2008.
• David Poole, "The Independent Choice Logic and Beyond", in Luc De Raedt, Paolo Frasconi, Kristian Kersting, and Stephen Muggleton (eds), Probabilistic Inductive Logic Programming: Theory and Application, LNAI 4911, 2008.
• David Poole, "Learning, Bayesian Probability, Graphical Models, and Abduction", Peter Flach and Antonis Kakas, editors, Abduction and Induction: essays on their relation and integration, Kluwer, 2000, 153--168.
• David Poole, ``Who chooses the assumptions?'', in P. O'Rorke (Ed.) Abduction, AAAI/MIT Press, forthcoming, 1997. (This book was never published, but here is a draft of the paper I wrote).
• 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, ``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.
• 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.

Essays

• David Poole, Semantic Science: machine understandable scientific theories and data, 2007
• David Poole, Agents, Decisions, Beliefs, Preferences, Science and Politics, AAAI Fellows Symposium, Cambridge, July 2006.

Non-refereed Journal Contributions

• 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.
• 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.
• D. L. Poole and R. G. Goebel, ``On Eliminating loops in Prolog'', SIGPLAN Notices, Vol 20, No 8, August 1985, pp. 38-40,

Workshops

• Clinton Smyth, David Poole and Rita Sharma, ``Semantic e-Science and Geology'', AAAI-07 Semantic e-Science workshop, 2007.
• Rita Sharma, David Poole and Clinton Smyth, ``A System of Ontologically-Grounded Probabilistic Matching'', Uncertainty in AI, Applications Workshop, July 2007.
• Michael Chiang and David Poole, ``Dynamic Predicate Construction for Learning Relational Concepts'', Work-in-Progress Proceedings of the 2007 International Conference on Inductive Logic Programming, June 2007.
• David Poole, Logical Argumentation, Abduction and Bayesian Decision Theory: A Bayesian Approach to Logical Arguments and its Application to Legal Evidential Reasoning, invited talk, Cardozo Conference on AI and Judicial Proof, New York, Aprol 2000.
• C. Boutilier, R. Brafman, C. Geib and David Poole, ``A Constraint-Based Approach to Preference Elicitation and Decision Making'', AAAI Spring Symposium on Qualitative Decision Theory, Stanford, March 1997.
• M. Horsch and David Poole, ``Flexible Construction of Decision Functions using Information Refinement'', Proc AAAI Fall Symposium on Felxible Compuation in Intelligent Systems: Results, Issues and Opportunities, MIT, Cambridge, Mass, November 1996, 68-72.
• David Poole, ``Sensing and Acting in the Independent Choice Logic'', Working Notes AAAI Spring Symposium 1995 -- Extending Theories of Actions: Formal Theory and Practical Applications, Stanford, March 1995, 163-168.
• 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.
• 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.
• David Poole, ``Minimalist AI and the Theorist conjecture'', AAAI Workshop on Defeasible Reasoning with Specificity and Multiple Inheritance, St. Louis, April 1989.
• 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.