Click here for abstracts.
[60.] Limits on the Use of Simulation in Physical Reasoning, by Ethan Ludwin-Peery, Neil Bramley, Ernest Davis, and Todd Gurekis. Cognitive Science, 2019.
[59.] Proof Verification Technology and Elementary Physics. In Algorithms and Complexity in Mathematics, Epistemology, and Science, N. Fillion, R. Corless, and I.S. Kotsireas (eds.) Springer, 2019.
[58.] ``Causal model'' must be broadly construed. by Ernest Davis and Gary Marcus. Response to Building machines that learn and think like people, by B. Lake, T. Ullman, J.B. Tenenbaum, and S. Gershman, Behavioral and Brain Sciences, 40,, 2017.
[57.] Commonsense Reasoning about Containers using Radically Incomplete Information, by Ernest Davis, Gary Marcus and Noah Frazier-Logue, AI Journal, July 2017, 248, 46-84. PDF Word Journal version.
[56.] The Scope and Limits of Simulation in Cognitive Models by Ernest Davis and Gary Marcus, arXiv 1506.04956. June 2015. Word version.
[55.] Still searching for Principles: A Response to Goodman et al. (2015) Psychological Science, April 2015, Vol. 26 pp. 542-544. Version in Word. [A response to Relevant and Robust: A Response to Marcus and Davis (2013) by Noah Goodman et al.]
[54.] A difference of a factor of 70,000 between hit counts and results returned in Google Unpublished technical note. January 2015.
[53.] Bounding changes in probability over time: It is unlikely that you will change your mind very much very often. Unpublished, November 10, 2013.
[52.] The Relevance of Proofs of the Rationality of Probability Theory to Automated Reasoning and Cognitive Models. Unpublished.
[51.] Reasoning from Radically Incomplete Information: The Case of Containers. by Ernest Davis, Gary Marcus, and Angelica Chen. Advances in Cognitive Systems, 2013, 283-288.
[50.] The Scope and Limits of Simulation in Automated Reasoning, by Ernest Davis and Gary Marcus, Artificial Intelligence, 233, April 2016, 60-72. .
How robust are probabilistic models of higher-level cognition?
by Gary Marcus and Ernest Davis.
Psychological Science, Vol. 24, No. 12, 2013, 2351-2360.
Paper in Word.
Supplement in Word.
The Hypothesis Space in Gweon, Tenenbaum, and Schulz
[48.] The Expressive Power of First-Order Topological Languages. Journal of Logic and Computation, Vol. 23, No. 5, 2013, 1107-1141. Non-paywalled version .
[47.] A Qualitative Calculus for Three-Dimensional Rotations by Azam Asl and Ernest Davis. Spatial Cognition and Computation 14:1, 2014, 18-57. Journal version.
[46.] The Winograd Schema Challenge, by Hector Levesque, Ernest Davis, and Leora Morgenstern. KR-2012.
[45.] Elementarily Equivalent Structures for Topological Languages over Regions in Euclidean Space Journal of Logic and Computation, 23:3, 2013, 457-471. Journal Article
Qualitative Spatial Reasoning in Interpreting Text and Narrative.
Spatial Cognition and Computation, 13:4, 2013, 264-294.
John Bateman's response to me.     My response to Bateman.
[43.] Preserving Geometric Properties in Reconstructing Regions from Internal and Nearby Points. Computational Geometry: Theory and Applications, 45:5-6, 2012, 234-253. Link to journal article (Science Direct).
[42.] Qualitative Reasoning and Spatio-Temporal Continuity. This chapter appears in Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions edited by S. Hazarika, copyright 2012, IGI Global.
[41.] Ontologies and Representations of Matter. AAAI-10.
Pouring Liquids: A Study in Commonsense
Physical Reasoning Artificial Intelligence, vol. 172,
2008, pp. 1540-1578.
There is an
appendix containing the formal object-level proof of the main example.
Erratum in journal version (the correction is incorporated in the local version above).
[39.] How Does a Box Work? A Study in the Qualitative Dynamics of Solid Objects Artificial Intelligence , 175, 2011, 299-345. Official electronic version. There is an appendix containing the formal object-level proof of the main example.
[38.] The Expressivity of Quantifying over Regions. Journal of Logic and Computation. vol. 16, 2006, pp. 891-916.
A First-Order Theory of Communication and Multi-Agent Plans. By
Ernest Davis and Leora Morgenstern.
Journal of Logic and Computation, Vol. 15, No. 5, 2005, pp. 701-749.
Appendix A: Changes to the theory and consistency proof from ``Knowledge and Communication: A First-Order Theory.''
In Postscript. in PDF.
Appendix B: Proof of correctness of sample plan. in Postscript. in PDF.
Knowledge and Communication: A First-Order Theory.
Artificial Intelligence, vol. 166, 2005, pp. 81-140.
Paper in PDF. Journal-length version of (34).
[35.] Processes and Continuous Change in a SAT-based Planner. Ji-Ae Shin and Ernest Davis. Artificial Intelligence, vol. 166, 2005, pp. 194-253. Journal-length version of (33).
A First-Order Theory of Communicating First-Order Formulas,
KR-04. Conference-length version of (36).
Paper in Postscript. Paper in PDF.
Power-point presentation (Zipped directory with a .ppt and several .wav files).
[33.] Continuous Time in a SAT-Based Planner. By Ji-Ae Shin and Ernest Davis. AAAI-04, pp. 531-536. Conference-length version of (35). Paper in Postscript . Paper in PDF .
Continuous Shape Transformation and Metrics on Regions.
Informaticae, . Vol. 46, Nos. 1-2, 2001, pp. 31-54
An appendix to this paper is Describing spatial transitions using mereotopological relations over histories. NYU Computer Science Tech. Report 2000-809, October 2000.
[31.] Constraint Networks of Topological Relations and Convexity E. Davis, N.M. Gotts, and A.G. Cohn) CONSTRAINTS Vol. 4 No. 3, 1999, pp. 241-280.
[30.] Order of Magnitude Comparisons of Distance. In Journal of AI Research vol. 10, 1999, pp. 1-38.
[29.] The Naive Physics Perplex AI Magazine, vol. 19, no. 4, Winter 1998, pp. 51-79.
[28.] A Highly Expressive Language of Spatial Constraints. NYU Computer Science Tech. Report. 714.
[27.] Approximation and Abstraction in Solid Object Kinematics. NYU Computer Science Tech. Report. 706.
[26.] Approximations of Shape and Configuration Space NYU Computer Science Tech. Report. 703. A very much improved but unpublished (except for here) version, from 2007, is Kinematic Tolerance and the Topology of Configuration Space (See Abstracts for the curious history of this paper.)
[25.] Knowledge Preconditions for Plans. Journal of Logic and Computation, vol. 4, no. 5, Oct. 1994, pp. 721-766
[24.] Branching Continuous Time and the Semantics of Continuous Action. Second International Conference on AI Planning Systems, 1994.
[23.] The Kinematics of Cutting Solid Objects. Annals of Mathematics and Artificial Intelligence, vol. 9, no. 3,4, 1993, pp. 253-305.
[22.] Semantics for Tasks that can be Interrupted or Abandoned. First International Conference on AI Planning Systems, 1992.
[21.] Axiomatizing Qualitative Process Theory. Third International Conference on Knowledge Representation and Reasoning, 1992, pp.~177-188.
[20.] Infinite Loops in Finite Time: Some Observations.i Third International Conference on Knowledge Representation and Reasoning, 1992.
[19.] Lucid Representations. Tech. Rep. 565, NYU Comp. Sci. Dept., June 1991.
[18.] Physical Idealization as Plausible Inference. Tech. Rep. 534, NYU Comp. Sci. Dept., December, 1990. Logical Formalisms of Commonsense Reasoning, Stanford Spring Symposium, 1991.
Order of Magnitude Reasoning in Qualitative Differential Equations.
in J. de Kleer and D. Weld (eds.),
Readings in Qualitative Physical Reasoning
Morgan Kaufmann, 1989, pp. 424-434.
Table 1 in plain text.
[16.] Solutions to a Paradox of Perception with Limited Acuity. First International Conference on Knowledge Representation and Reasoning, 1989.
[15.] Reasoning about Hand-Eye Coordination. IJCAI-89 Workshop on Knowledge, Perception, and Planning
[14.] A Logical Framework for Commonsense Predictions of Solid Object Behavior. AI in Engineering, vol. 3 no. 3, 1988, pp. 125-140. This appeared in somewhat different form as A Framework for Qualitative Reasoning about Solid Objects,
[13.] Inferring Ignorance from the Locality of Visual Perception. Proc. AAAI-88, pp. 786-790
[12.] Error Correction in Cognitive Maps. Proc. Workshop on Sensor Fusion: Spatial Reasoning and Scene Interpretation, SPIE, 1988.
[11.] Constraint Propagation with Interval Labels. Artificial Intelligence, vol. 32, 1987, pp. 281-331.
[10.] Limits and Inadequacies in Artificial Intelligence. In No Way: On the Nature of the Impossible, Philip Davis and David Park, (eds.), W.H. Freeman, 1987, pp. 90-110
[9.] A Representation for Complex Physical Domains. By S. Addanki and E. Davis. Proceedings of the 9th IJCAI, pp. 443 - 446, 1985
[8.] Planning and Executing Routes through Uncertain Territory. By D. McDermott and E. Davis, Artificial Intelligence, vol. 22, pp. 107 - 156, 1984
[7.] A High Level Real-Time Programming Language Tech. Rep. 145, NYU Comp. Sci. Dept., October 1984
[6.] Shape and Function of Solid Objects: Some Examples Tech. Rep 137, NYU Comp. Sci. Dept., October 1984
[5.] An Ontology of Physical Action. Tech. Rep. 123, NYU Comp. Sci. Dept., June 1984
[4.] The MERCATOR Representation of Spatial Knowledge. IJCAI-83
[3.] What's the Point? By R. Schank, G. Collins, E. Davis, P. Johnson, S. Lytinen, and B. Reiser. Cognitive Science, Vol. 6, No. 3, 1982
[2.] Algorithms for Scheduling Tasks on Unrelated Processors. By E. Davis and J. Jaffe. JACM, Vol. 28 No. 4, October 1981
[1.] Organizing Spatial Knowledge Tech. Report 193, Yale Computer Science Dept., January 1981