Abstract
The main objective of this paper is to characterize types of knowledge that can be represented by models and to identify small models that enable efficient computation. The logical models in question represent knowledge bases, a knowledge base being a set of facts known to some agent (e.g., the actual knowledge of a player in a game). Any piece of information contained in a knowledge base is verified by the corresponding model. The objective is not merely to represent or retrieve basic facts, but also to infer new facts or knowledge following from the knowledge base. Thus, the supposition is that a model characterizes a knowledge base if everything which follows from it is true in the model, and vice versa. Likewise, a query can be answered by checking whether a related proposition is true in the model. Since (at least for human reasoners) model checking is a relatively simple activity, the method is quite appealing.
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Thijsse, E. (1997). Knowledge and Belief Representation in a Partial Model. In: Bacharach, M., Gérard-Varet, LA., Mongin, P., Shin, H.S. (eds) Epistemic Logic and the Theory of Games and Decisions. Theory and Decision Library, vol 20. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1139-3_6
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DOI: https://doi.org/10.1007/978-1-4613-1139-3_6
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