Some publications

Book

Elements of Scientific Inquiry. E. Martin and D. Osherson. The MIT Press, 1998.

Book chapters

• A first-order framework for learning. D. Osherson, D. de Jongh, E. Martin, and S. Weinstein. In Handbook of Logic and Language. J. van Benthem and Alice ter Meulen (eds.). The MIT Press, North Holland, 1996.

• Deduction, Induction and Beyond in Parametric Logic. E. Martin, A. Sharma and F. Stephan. In Induction, Algorithmic Learning Theory, and Philosophy. M. Friend, N. Goethe and V. Harizanov (eds.). Series Logic, Epistemology, and the Unity of Science, vol. 9. p 55-110. Dordrecht, Springer, 2007.

• Humans and Machines: Nature of Learning and Learning of Nature. H. Hagege, C. Dartnell, E. Martin and J. Sallantin. In Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence. Y. Wang. (ed.). Series Advances in Cognitive Informatics and Natural Intelligence. Chap. 5, P. 71-91. Information Science Reference, 2009.

Journal papers

• Spatial Proximity is more than just a Distance Measure J. Brennan and E. Martin. International Journal of Human-Computer Studies, 70:88-106, 2012.

• Input-Dependence in Function-Learning S. Jain, E. Martin and F. Stephan. Theory of Computing Systems, 45(4):849-864, 2009.

• Human Discovery and Machine Learning C. Dartnell, E. Martin, H. Hagege and J. Sallantin. International Journal of Cognitive Informatics and Natural Intelligence, 2(4):55-69, 2008.

• Absolute Versus Probabilistic Classification in a Logical Setting S. Jain, E. Martin and F. Stephan. Theoretical Computer Science, 397(1-3):114-128, 2008.

• On the Data Consumption Benefits of Accepting Increased Uncertainty. E. Martin, A. Sharma and F. Stephan. Theoretical Computer Science, 382(3):170-182, 2007.

• Identifying Clusters from Positive Data. J. Case, S. Jain, E. Martin, A. Sharma and F. Stephan. SIAM Journal on Computing. 36(1):28-55, 2006.

• On ordinal VC-dimension and some notions of complexity. E. Martin, A. Sharma and F. Stephan. Theoretical Computer Science. 364(1):62-76, 2006.

• Unifying Logic, Topology and Learning in Parametric Logic. E. Martin, A. Sharma and F. Stephan. Theoretical Computer Science. 350(1):102-124, 2006.

• Learning Power and Language Expressiveness. E. Martin, A. Sharma and F. Stephan. Theoretical Computer Science. 298(2):365-383, 2003.

• Generalized Logical Consequence: Making room for induction in the logic of science. S. Chopra and E. Martin. Journal of Philosophical Logic, 31(3):245-280, 2002.

• Scientific Discovery from the Perspective of Hypothesis Acceptance. E. Martin and D. Osherson. Philosophy of Science, supplement to 69(3):S331-S341, 2002.

• Induction by enumeration. E. Martin and D. Osherson. Information and Computation, 171(1):50-68, 2001.

• Scientific Discovery on Positive Data via Belief Revision. E. Martin and D. Osherson. Journal of Philosophical Logic, 29(5):483-506, 2000.

• Belief revision in the service of scientific discovery. E. Martin and D. Osherson. Mathematical Social Sciences, 36(1):57-68, 1998.

• Scientific discovery based on belief revision. E. Martin and D. Osherson. Journal of Symbolic Logic, 62(4):1352-1370, 1997.

• Approches formelles de l'apprentissage. D. Andler, S. Boucheron et E. Martin. Le courrier du CNRS, vol. 79, 1992.

Conference papers

• A Dialectic Approach to Problem-Solving. E. Martin and J. Sallantin. In Proceedings of the 12th International Conference on Discovery Science. R. Goebel, J. Siekmann abd W. Wahlster (eds.): 417-424, LNCS 5808, Springer, 2009.

• Learning from Each Other. C. Dartnell, E. Martin and J. Sallantin. In Proceedings of the 11th International Conference on Discovery Science. R. Goebel, J. Siekmann abd W. Wahlster (eds.): 148-159, LNCS 5255, Springer, 2008.

• Learning a Plan in the Limit. P. Caldon and E. Martin. Proceedings of the AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning. The AAAI Press, Technical Report SS-07-05: 25-34, 2007.

• Quantification over names and modalities. E. Martin. Advances in Modal Logic, vol 6: 353-372. G. Governatori, I. Hodkinson and Y. Venema (eds.), College Publications, 2006.

• Membership Functions for Spatial Proximity. J. Brennan and E. Martin. In Proceedings of the 19th Australian Joint Conference on Artificial Intelligence, AI2006: 942-949. A. Sattar and B.-H. Kang (eds.):942-949. LNCS 4304, Springer, 2006.

• On a Syntactic Characterization of Classification with a Mind Change Bound E. Martin and A. Sharma. In Proceedings of the 18th Annual Conference on Learning Theory, COLT 2005. P. Auer and R. Meir (eds.):413-428, LNAI 3559, Springer, 2005.

• Psychology looks hopefully to logic D. Osherson and E. Martin. In Proceedings of the Annual European Summer Meeting of the Association for Symbolic Logic. R. Cori, A. Razborov, S. Todorcevic and C. Wood (eds.):323-334, Lecture Notes in Logic 19, Association for Symbolic Logic, 2005.

• On the Convergence of Incremental Knowledge Base Construction T. Cao, E. Martin and P. Compton. In Proceedings of the 7th International Conference on Discovery Science. E. Suzuki and S. Arikawa (eds.):207-218, LNAI 3245, Springer, 2004.

• Developing an ontology of spatial relations J. Brennan, E. Martin and M. Kim In Visual and Spatial Reasoning in Design III, J. Gero, B. Tversky and T. Knight (eds.): 163-182, Key Centre of Design Computing and Cognition, Sydney, 2004.

• Limiting Resolution: from Foundations to Implementation. P. Caldon and E. Martin. In Proceedings of the 20th International Conference on Logic Programming, B. Demoen and V. Lifschiftz (eds.): 149-164, LNCS 3132, Springer, 2004.

• A Theory of Proximity Relations. J. Brennan, E. Martin and W. Wilson: A Theory of Proximity Relations. In Proceedings of the Joint International Conference on Cognitive Science (ICCS/ASCS), vol. 1:65-70, University of New South Wales, 2003.

• Learning, Logic, and Topology in a Common Framework. E. Martin, A. Sharma, and F. Stephan. In Proceedings of the 13th International Conference on Algorithmic Learning Theory. N. Cesa-Bianchi, M. Numao, and R. Reischuk (eds.). LNAI 2533, Springer, 2002.

• Learning in Logic with RichProlog. E. Martin, P. Nguyen, A. Sharma, and F. Stephan. In Proceedings of the 18th International Conference on Logic Programming. P. Stuckey (ed.). LNCS 2401, Springer, 2002.

• Foundations for a Formalism of Nearness. J. Brennan and E. Martin. In Proceedings of AI2002: Advances in Artificial Intelligence. B. McKay and J. Slaney (eds.). LNAI 2557, Springer, 2002.

• On Sufficient Conditions for Learnability of Logic Programs from Positive Data. E. Martin and A. Sharma. In Proceedings of the 9th International Conference on Inductive Logic Programming. S. Dzeroski and P. Flach (eds.). LNCS 1634, Springer, 1999.

• Scientific discovery based on belief revision. E. Martin and D. Osherson. In Proceedings of the 4th International Symposium on Artificial Intelligence and Mathematics. H. Kautz and B. Selman (eds.). 1996.

• Scientific discovery via rational hypothesis revision. D. Osherson and E. Martin. In Proceedings of the 10th International Congress of Logic, Methodology, and Philosophy of Science. J. van Benthem, M. Dalla Chiara, K. Doets and D. Mundici (eds.), 1995.

• A note on the use of probabilities by mechanical scientists. E. Martin and D. Osherson. In Proceedings of the 2nd European Conference on Computational Learning Theory P. Vitanyi (ed.). LNAI 904, Springer, 1995.

• Intelligent Control: a theoretical framework. D. Luzeaux and E. Martin. In Proceedings of the 3rd SIAM Conference on Control and its applications. 1995.

• Computability in control. E Martin and D Luzeaux. In Proceedings of the 3rd International Symposium on Artificial Intelligence and Mathematics. 1994.

• Oracles for learning programs. E. Martin. In Proceedings of the IEEE Systems Man Cybernetics Conference. 1993.

• Steps or stages for incremental control? D. Luzeaux and E. Martin. In Proceedings of the AAAI Symposium on training issues in incremental learning. 1993.

• Learning and control from a recursive viewpoint. E. Martin, D. Luzeaux, and B. Zavidovique. In Proceedings of the IEEE International Symposium on Intelligent Control. 1992.

• Apprentissage pour le controle de processus: aspects theoriques. D. Luzeaux, E. Martin, and B. Zavidovique. Journees Franccaises de l'Apprentissage no 6. 1991.