Abstract
An implemented context-based reasoning system called ATT-Meta is sketched. The system can perform both reasoning about beliefs of agents and metaphor-based reasoning. In particular, it can perform metaphor-based reasoning about beliefs and reasoning acts. The metaphor-based reasoning and belief reasoning facilities are fully integrated into a general framework for uncertain reasoning. This framework allows for uncertain reasoning and conflict resolution within individual contexts, uncertainty in individual inter-context bridging rules, conflict resolution between the effects of different bridging rules, and conflictresolution across context boundaries when argumentation inside a context conflicts with argumentation outside.
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References
Barnden, J.A. (1998). Uncertain reasoning about agents’ beliefs and reasoning. Technical Report CSRP-98-11, School of Computer Science, The University of Birmingham, U.K. Also in Artificial Intelligence and Law, in press.
Barnden, J.A., Helmreich, S., Iverson, E. & Stein, G.C. (1994). An integrated implementation of simulative, uncertain and metaphorical reasoning about mental states. In J. Doyle, E. Sandewall & P. Torasso (Eds), Principles of Knowledge Representation and Reasoning: Proceedings of the Fourth International Conference, pp.27–38. San Mateo, CA: Morgan Kaufmann.
Creary, L. G. (1979). Propositional attitudes: Fregean representation and simulative reasoning. Procs. 6th. Int. Joint Conf. on Artificial Intelligence (Tokyo), pp.176–181. Kaufmann.
Fauconnier, G. & Turner, M. (1998). Conceptual integration networks. Cognitive Science, 22(2), pp.133–187.
Hobbs, J.R. (1990). Literature and cognition. CSLI Lecture Notes, No. 21, Center for the Study of Language and Information, Stanford University.
Lakoff, G. (1993). The contemporary theory of metaphor. In A. Ortony (Ed.), Metaphor and Thought, 2nd edition, pp.202–251. Cambridge, U.K.: Cambridge University Press.
Loui, R.P., Norman, J., Olson, J. & Merrill, A. (1993). A design for reasoning with policies, precedents, and rationales. In Fourth International Conference on Artificial Intelligence and Law: Proceedings of the Conference, pp.202–211. New York: ACM.
Martin, J. (1994). Metabank:A knowledge-base of metaphoric language conventions. Computational Intelligence, 10(2), pp.134–149.
Narayanan, S. (1997). KARMA: Knowledge-based action representations for metaphor and aspect. Ph.D. thesis, EECS Department, U. of California, Berkeley, August 1997.
Parsons, S., Sierra, C. & Jennings, N. (1998). Multi-context argumentative agents. In Working Papers of the 4th Symp. on Logical Formalizations of Commonsense Reasoning, London.
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© 1999 Springer-Verlag Berlin Heidelberg
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Barnden, J.A., Lee, M.G. (1999). An Implemented Context System that Combines Belief Reasoning, Metaphor-Based Reasoning and Uncertainty Handling. In: Bouquet, P., Benerecetti, M., Serafini, L., Brézillon, P., Castellani, F. (eds) Modeling and Using Context. CONTEXT 1999. Lecture Notes in Computer Science(), vol 1688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48315-2_3
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DOI: https://doi.org/10.1007/3-540-48315-2_3
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