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Weighted abduction for plan ascription

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Abstract

We describe an approach to abductive reasoning calledweighted abduction, which uses inference weights to compare competing explanations for observed behavior. We present an algorithm for computing a weighted-abductive explanation, and sketch a model-theoretic semantics for weighted abduction. We argue that this approach is well suited to problems of reasoning about mental state. In particular, we show how the model of plan ascription developed by Konolige and Pollack can be recast in the framework of weighted abduction, and we discuss the potential advantages and disadvantages of this encoding.

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Author notes

  1. Martha E. Pollack

    Present address: Department of Computer Science, University of Pittsburgh, 15260, Pittsburgh, PA, USA

Authors and Affiliations

  1. Artificial Intelligence Center, 333 Ravenswood Ave., 94025, Menlo Park, CA, USA

    Douglas E. Appelt & Martha E. Pollack

  2. Center for the Study of Language and Information, SRI International, 333 Ravenswood Ave., 94025, Menlo Park, CA, USA

    Douglas E. Appelt & Martha E. Pollack

Authors
  1. Douglas E. Appelt
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  2. Martha E. Pollack
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Additional information

Dr. Douglas E. Appelt is a Senior Computer Scientist in the Artificial Intelligence Center at SRI International, as well as a research affiliate at the Center for the Study of Language and Information. He received a B.A. degree in Computer Science from Michigan State University, and M.S. and Ph.D. degrees in Computer Science from Stanford University. Dr. Appelt has published a book and numerous technical papers about the application of problem solving techniques and speech-act theory to the generation and understanding of natural language.

Dr. Martha E. Pollack received her B.A. degree in Linguistics from Dartmouth College, and her M.S.E.E. and Ph.D. degrees in Computer and Information Science from the University of Pennsylvania. Since 1985, she has been a Computer Scientist at the Artificial Intelligence Center at SRI International, and a Senior Researcher at the Center for the Study of Language and Information. She is also Consulting Assistant Professor of Computer Science at Stanford University. She has conducted research and published papers in theories of rational action, plan generation and plan recognition, experimental evaluation of AI systems, and natural-language semantics and pragmatics.

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Appelt, D.E., Pollack, M.E. Weighted abduction for plan ascription. User Model User-Adap Inter 2, 1–25 (1992). https://doi.org/10.1007/BF01101857

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