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  1. (1 other version)Prolegomena to dynamic logic for belief revision.Hans P. Van Ditmarsch - 2005 - Synthese 147 (2):229-275.
    In ‘belief revision’ a theory is revised with a formula φ resulting in a revised theory . Typically, is in , one has to give up belief in by a process of retraction, and φ is in . We propose to model belief revision in a dynamic epistemic logic. In this setting, we typically have an information state (pointed Kripke model) for the theory wherein the agent believes the negation of the revision formula, i.e., wherein is true. The revision with (...)
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  • Dynamic Formal Epistemology.Patrick Girard, Olivier Roy & Mathieu Marion (eds.) - 2010 - Berlin, Germany: Springer.
    This volume is a collation of original contributions from the key actors of a new trend in the contemporary theory of knowledge and belief, that we call “dynamic epistemology”. It brings the works of these researchers under a single umbrella by highlighting the coherence of their current themes, and by establishing connections between topics that, up until now, have been investigated independently. It also illustrates how the new analytical toolbox unveils questions about the theory of knowledge, belief, preference, action, and (...)
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  • A model for updates in a multi-agent setting.John Cantwell - 2007 - Journal of Applied Non-Classical Logics 17 (2):183-196.
    A formal model for updates—the result of learning that the world has changed—in a multi-agent setting is presented and completely axiomatized. The model allows that several agents simultaneously are informed of an event in the world in such a way that it becomes common knowledge among the agents that the event has occurred. The model shares many features with the model for common announcements—an announcement about the state of the world in which it becomes common knowledge among the audience that (...)
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  • Uncertainty, Rationality, and Agency.Wiebe van der Hoek - 2006 - Dordrecht, Netherland: Springer.
    This volume concerns Rational Agents - humans, players in a game, software or institutions - which must decide the proper next action in an atmosphere of partial information and uncertainty. The book collects formal accounts of Uncertainty, Rationality and Agency, and also of their interaction. It will benefit researchers in artificial systems which must gather information, reason about it and then make a rational decision on which action to take.
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