Earlier Writing

Book

  • John R. Josephson and Susan G. Josephson, ed., (1994, 1996) Abductive Inference: Computation, Philosophy, Technology, Cambridge University Press.

Book Chapters

  • John R. Josephson, (2000) “Smart Inductive Generalizations are Abductions” Abduction and Induction, P. A. Flach and A. C. Kakas (eds.), Kluwer, Netherlands.
  • Iyer, N. S., Josephson, J. R. (2001). “Multicriterially Best Explanations” In Discovery Science, (eds. K.P. Jantke and A. Shinohara), pp. 128-140, Lecture Notes in Artificial Intelligence 2226, New York, NY: Springer-Verlag. ISBN 3-540-42956-5.

Journal Articles

  • Vivek Bharathan & John R. Josephson, (2006) “Belief Revision controlled by Meta-Abduction,” Special Issue of Logic Journal of IGPL on Abduction, Practical Reasoning, and Creative Inferences in Science, edited by L. Magnani, Volume 14, Number 2, pp. 271-285, Oxford University Press.
  • John R. Josephson (2001). On the Proof Dynamics of Inference to the Best Explanation. Cardozo Law Review, Volume 22, Numbers 5-6, July 2001. Reprinted in The Dynamics of Judicial Proof: Computation, Logic, and Common Sense, edited by Marilyn T. MacCrimmon and Peter Tillers, Physica-Verlag, Heidelberg, 2002 (pp. 287-306).
  • John R. Josephson (1998). Abduction-Prediction Model of Scientific Discovery Reflected in a Prototype System for Model-Based Diagnosis. Philosophica, 61(1), 9-17.
  • Ashok K. Goel, John R. Josephson, Olivier Fischer, and P. Sadayappan, “Practical Abduction: Characterization, Decomposition, and Concurrency,” in The Journal of Theoretical and Experimental Artificial Intelligence, Vol. 7, 1995, 429-450.
  • Michael C. Tanner and John R. Josephson, “The Role of Explanatory Relationships in Strategies for Abduction,” IEEE Expert , Vol. 2, Number 3, June 1994, pp. 54-59.
  • Tom Bylander, Dean Allemang, Michael C. Tanner, and John R. Josephson, “The Computational Complexity of Abduction,” in Artificial Intelligence, Vol. 49, 1991, pp. 25–60; reprinted in Knowledge Representation edited by Brachman, Levesque, and Reiter, MIT Press, 1992, pp. 25–60.
  • John Josephson, “Inference to the Best Explanation is Basic,” appears in Behavioral and Brain Sciences as a commentary on “Explanatory Coherence” by Paul Thagard, Vol. 12, No. 3, September 1989.
  • J. Josephson, B. Chandrasekaran, J. Smith and M. Tanner, “A Mechanism for Forming Composite Explanatory Hypotheses,” appears in IEEE Transactions on Systems, Man & Cybernetics, Special Issue on Causal and Strategic Aspects of Diagnostic Reasoning, Vol. SMC-17, No. 3, May/June, 1987, pp. 445-454.

Conference Proceedings

  • John R. Josephson, Joshua Eckroth, and Timothy Miller, “Estimation of adversarial social networks by fusion of information from a wide range of sources,” in the Proceedings of the 12th International Conference on Information Fusion, Fusion 2009, Seattle, July 2009, pp. 2144-2152.
  • John R. Josephson, “Abductive Inferencing for Integrating Information from Human and Robotic Sources,” Proceedings of Fusion 2008 – the 11th International Conference on Information Fusion, June 30 – July 03, 2008, Cologne, Germany.
  • Bharathan, V and Josephson, J. “An Abductive Framework for Level One Information Fusion,” Proceedings of Fusion 2006: The 9th International Conference on Information Fusion, Florence (Italy), 10-13 July 2006.
  • B. Chandrasekaran and John R. Josephson, “Representing Function as Effect: Assigning Functions to Objects in Context and Out,” Workshop on Modeling and Reasoning about Function at the 1996 National Conference on Artificial Intelligence – AAAI’96, Aug. 4-8, Portland Oregon.
  • Josephson, J. R. (1995). Formation of Well-Justified Composite Explanatory Hypotheses Despite the Threat of Combinatorial Explosion. In R. Valdez-Perez (Ed.), AAAI Spring Symposium on Systematic Methods of Scientific Discovery, (pp. 133-138). Stanford, CA: AAAI. AAAI Technical Report
  • Richard Fox and John Josephson, “The use of explicit noise hypotheses in forming composite explanations,” appears in SPIE Proceedings for Neural and Stochastic Methods in Image and Signal Processing II, Volume 2032, p 245-255, published in Bellingham, Washington, 98227-0100; the conference was held in San Diego CA, July 1993.
  • John R. Josephson, Tom Bylander, and Diana Smetters “An Architecture for Knowledge System Development: The Integrated Generic Task Toolset,” AAAI-89 Symposium Series, March 28-30, 1989; appears in the Working Notes of the Symposium on Knowledge System Development Tools and Languages.
  • John Josephson, “Speech Understanding Based on Layered Abduction: Working Notes for the Symposium on Spoken Language Systems,” AAAI-89 Spring Symposium Series, Stanford University, March 28-30, 1989; appears in the Working Notes of the Symposium.
  • John Josephson, “A Layered Abduction Model of Perception: Integrating Bottom-up and Top-down Processing in a Multi-Sense Agent,” in the Proceedings of the NASA Conference on Space Telerobotics, Pasadena, California, January 31-February 2, 1989, vol. IV, pp. 197-206.
  • M. C. Tanner and John Josephson, “Justifying Diagnostic Conclusions,” presented at the AAAI-88 Workshop on Explanation, August 22, 1988, and appears in the Workshop Proceedings, pp. 76-79.
  • John R. Josephson “Reducing Uncertainty by Using Explanatory Relationships,” appears in the Proceedings of the Space Operations Automation & Robotics-1988 (SOAR-88) Workshop , Dayton, Ohio, July 22, 1988, sponsored by NASA, the U.S. Air Force, and Wright State University, pp. 149-151.
  • Ashok Goel, P, Sadayappan and John R. Josephson, “Concurrent Synthesis of Composite Explanatory Hypotheses,” presented at the Seventeenth International Conference on Parallel Processing, St. Charles, Illinois, August 15-19, 1988; appears in the conference proceedings, pp. 156-160.
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