Abstract
We propose a general formulation of reasoning about action based on prioritized logic programming, where defeasibility handling is explicitly taken into account. In particular, we consider two types of defeasibilities in our problem domains: defeasible constraints and defeasible observations. By introducing the notion of priority in action formulation, we show that our approach provides a unified framework to handle these defeasibilities in temporal prediction and postdiction reasoning with incomplete information.
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© 1998 Springer-Verlag Berlin Heidelberg
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Zhang, Y. (1998). Representing defeasible constraints and observations in action theories. In: Antoniou, G., Slaney, J. (eds) Advanced Topics in Artificial Intelligence. AI 1998. Lecture Notes in Computer Science, vol 1502. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095062
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DOI: https://doi.org/10.1007/BFb0095062
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