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Using Abstract Resources to Control Reasoning

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Abstract

Many formalisms for reasoning about knowing commit an agent to be logically omniscient. Logical omniscience is an unrealistic principle for us to use to build a real-world agent, since it commits the agent to knowing infinitely many things. A number of formalizations of knowledge have been developed that do not ascribe logical omniscience to agents. With few exceptions, these approaches are modifications of the “possible-worlds” semantics. In this paper we use a combination of several general techniques for building non-omniscient reasoners. First we provide for the explicit representation of notions such as problems, solutions, and problem solving activities, notions which are usually left implicit in the discussions of autonomous agents. A second technique is to take explicitly into account the notion of resource when we formalize reasoning principles. We use the notion of resource to describe interesting principles of reasoning that are used for ascribing knowledge to agents. For us, resources are abstract objects. We make extensive use of ordering and inaccessibility relations on resources, but we do not find it necessary to define a metric. Using principles about resources without using a metric is one of the strengths of our approach.

We describe the architecture of a reasoner, built from a finite number of components, who solves a puzzle, involving reasoning about knowing, by explicitly using the notion of resource. Our approach allows the use of axioms about belief ordinarily used in problem solving – such as axiom K of modal logic – without being forced to attribute logical omniscience to any agent. In particular we address the issue of how we can use resource-unbounded (e.g., logically omniscient) reasoning to attribute knowledge to others without introducing contradictions. We do this by showing how omniscient reasoning can be introduced as a conservative extension over resource-bounded reasoning.

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References

  • Aiello, L., Nardi, D., and Schaerf, M., 1991, “Reasoning about reasoning in a meta-level architecture,” Journal of Applied Intelligence 1, 55–67.

    Google Scholar 

  • Attardi, G. and Simi, M., 1984, “Metalanguage and reasoning across viewpoints,” pp. 315–324 in Proceedings of the European Conference on Artificial Intelligence, Pisa, T. O'shea, ed., Amsterdam: Elsevier Science Publishers.

    Google Scholar 

  • Attardi, G. and Simi, M., 1998, “Communication across viewpoints,” Journal of Logic, Language and Information 7, 53–75.

    Google Scholar 

  • Barwise, J., 1981, “Scenes and other situations,” Journal of Philosophy LXXVIII(7), 369–397.

    Google Scholar 

  • Buvač, S., 1996, “Quantificational logic of context,” pp. 600–606 in Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI96), Menlo Park/Cambridge: AAAI Press/The MIT Press.

    Google Scholar 

  • Cadoli, M. and Schaerf, M., 1992, “Approximate reasoning and nonomniscient agents,” pp. 169–183 in Proceedings of the Fourth Conference on Theoretical Aspects of Reasoning about Knowledge (TARK-92), Y. Moser, ed., San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  • Elgot-Drapkin, J.J., 1991, “Steplogic and the three-wise-men problem,” pp. 412–417 in Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI91), Menlo Park/Cambridge: AAAI Press/The MIT Press.

    Google Scholar 

  • Elgot-Drapkin, J.J. and Perlis, D., 1990, “Reasoning situated in time I: Basic concepts,” Journal of Experimental and Theoretical Artificial Intelligence 2, 75–98.

    Google Scholar 

  • Elgot-Drapkin, J.J., Miller, M., and Perlis, D., 1991, “Memory, reason and time: The steplogic approach,” pp. 79–103 in Philosophy and AI: Essays at the Interface, R. Cummins and J. Pollock, eds., Cambridge, MA: MIT Press.

    Google Scholar 

  • Fagin, R., Halpern, J.Y., Moses, Y., and Vardi, M.Y., 1992, Reasoning about Knowledge, Cambridge, MA: MIT Press.

    Google Scholar 

  • Gamow, G. and Stern, M., 1958, Puzzle Math, Vintage Press.

  • Giunchiglia, F., 1991, “Multilanguage systems,” in Proceedings of AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning, Menlo Park: AAAI Press. Also IRST Technical Report No. 901117.

    Google Scholar 

  • Giunchiglia, F., 1993, “Contextual reasoning,” Epistemologia, Special Issue on I Linguaggi e le Macchine XVI, 345–364.

    Google Scholar 

  • Giunchiglia, F. and Serafini, L., 1994, ''Multilanguage hierarchical logics (or: how we can do without modal logics), Artificial Intelligence 65, 29–70.

    Google Scholar 

  • Giunchiglia, F. and Traverso, P., 1995, “A metatheory of a mechanized object theory,” Artificial Intelligence 80, 197–241.

    Google Scholar 

  • Giunchiglia, F. and Walsh, T., 1992, “A theory of abstraction,” Artificial Intelligence 56, 323–390.

    Google Scholar 

  • Halpern, J.Y. and Moses, Y., 1992, “A guide to completeness and complexity for modal logic of knowledge and belief,” Artificial Intelligence Journal 54, 319–379.

    Google Scholar 

  • Halpern, J.Y., 1991, “Reasoning about knowledge: A survey circa 1991,” in Encyclopedia of Computer Science and Technology, A.A. Kent and J.G. Williams, eds., Marcel Dekker. Preliminary version on Proceedings of the Conference on Theoretical Aspects of Reasoning about Knowledge (TARK), Morgan Kaufmann Publisher, 1986.

  • Halpern, J.Y. and Vardi, M.Y., 1991, “Model checking vs. theorem proving: A manifesto,” pp. 325–334 in Proceedings of the Second International Conference on the Principles of Knowledge Representation and Reasoning (KR91). Also in Lifshitz, V., 1991, Artificial Intelligence and Mathematical Theory of Computation. Papers in Honor of John McCarthy, San Diego, CA: Academic Press.

    Google Scholar 

  • Hintikka, J., 1962, Knowledge and Belief, Ithaca, NY: Cornell University Press.

    Google Scholar 

  • Kripke, S.A., 1963, “Semantical considerations on modal logic,” Acta Philosophica Fennica 16, 83–94.

    Google Scholar 

  • Levesque, H.J., 1984, “A logic of implicit and explicit belief,” pp. 198–202 in Proceedings of the Fourth National Conference on Artificial Intelligence (AAAI84), Los Altos, CA: William Kaufmann.

    Google Scholar 

  • Maes, P. and Nardi, D., eds., 1988, Meta-Level Architectures and Reflection, Amsterdam: Elsevier Science Publishers/North Holland.

    Google Scholar 

  • McCarthy, J., 1987, “Generality in artificial intelligence,” Communications of the ACM 30.

  • McCarthy, J. and Buvač, S., 1994, “Formalizing context (Expanded notes),” Technical Note STAN-CS-TN–94–13, Stanford University.

  • Montague, R., 1968, “Pragmatics,” pp. 101–121 in Contemporary Philosophy, R. Kalibansky, ed., La Nuova Italia Editrice.

  • Talcott, C.L. and Weyhrauch, R.W., 1990, “Towards a theory of mechanized reasoning I: FOL contexts, an extensional view,” pp. 634–639 in Proceedings of the 8th European Conference on Artificial Intelligence, (ECAI-90), L.C. Aiello, ed., London: Pitman.

    Google Scholar 

  • ter Meulen, A.G.B., 1995a, “Content in context,” pp. 97–101 in Formalizing Context, AAAI-95 Fall Symposium, Menlo Park: AAAI Press.

    Google Scholar 

  • ter Meulen, A.G.B., 1995b, Representing Time in Natural Language, Cambridge, MA: MIT Press.

    Google Scholar 

  • Weyhrauch, R.W., 1977, “A Users Manual for Fol,” Technical Report STAN-CS–77–432, Stanford University Computer Science Department.

  • Weyhrauch, R.W., 1980, “Prolegomena to a theory of formal reasoning,” Artificial Intelligence 13, 133–170.

    Google Scholar 

  • Weyhrauch, R.W. and Talcott, C.L., 1994, “The logic of FOL systems: Formulated in set theory,” pp. 119–132 in Festschrift in Honor of Professor Satoru Takasu, M. Hagiya, N. D. Jones, and M. Sato, eds., Lecture Notes in Computer Science, Vol. 792, Berlin: Springer-Verlag.

    Google Scholar 

  • Weyhrauch, R.W. and Talcott, C.L., 1995a “FOL home page,” URL = http://wwwformal. stanford.edu/FOL/home.html.

  • Weyhrauch, R.W. and Talcott, C.L., 1995b, “The logic of FOL systems: Introduction,” URL = http://www-formal. stanford.edu/FOL/home.html.

  • Weyhrauch, R.W. and Talcott, C.L., 1995c, “Problem solving contexts,” URL = http://www-formal. stanford.edu/FOL/home.html.

  • Weyhrauch, R.W., Cadoli, M., and Talcott, C.L., 1995, “Deducing logical omniscience,” URL = http://www-formal. stanford.edu/FOL/home.html.

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Weyhrauch, R.W., Cadoli, M. & Talcott, C.L. Using Abstract Resources to Control Reasoning. Journal of Logic, Language and Information 7, 77–101 (1998). https://doi.org/10.1023/A:1008275403912

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