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  1. Dynamic Update with Probabilities.Johan van Benthem, Jelle Gerbrandy & Barteld Kooi - 2009 - Studia Logica 93 (1):67 - 96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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  • DEL-sequents for regression and epistemic planning.Guillaume Aucher - 2012 - Journal of Applied Non-Classical Logics 22 (4):337 - 367.
    (2012). DEL-sequents for regression and epistemic planning. Journal of Applied Non-Classical Logics: Vol. 22, No. 4, pp. 337-367. doi: 10.1080/11663081.2012.736703.
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  • On axiomatizations of public announcement logic.Yanjing Wang & Qinxiang Cao - 2013 - Synthese 190 (S1).
    In the literature, different axiomatizations of Public Announcement Logic (PAL) have been proposed. Most of these axiomatizations share a “core set” of the so-called “reduction axioms”. In this paper, by designing non-standard Kripke semantics for the language of PAL, we show that the proof system based on this core set of axioms does not completely axiomatize PAL without additional axioms and rules. In fact, many of the intuitive axioms and rules we took for granted could not be derived from the (...)
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  • Logics of Communication and Change. van Benthem, Johan, van Eijck, Jan & Kooi, Barteld - unknown
    Current dynamic epistemic logics for analyzing effects of informational events often become cumbersome and opaque when common knowledge is added for groups of agents. Still, postconditions involving common knowledge are essential to successful multi-agent communication. We propose new systems that extend the epistemic base language with a new notion of ‘relativized common knowledge’, in such a way that the resulting full dynamic logic of information flow allows for a compositional analysis of all epistemic postconditions via perspicuous ‘reduction axioms’. We also (...)
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  • Conditional probability meets update logic.Johan van Benthem - 2003 - Journal of Logic, Language and Information 12 (4):409-421.
    Dynamic update of information states is a new paradigm in logicalsemantics. But such updates are also a traditional hallmark ofprobabilistic reasoning. This note brings the two perspectives togetherin an update mechanism for probabilities which modifies state spaces.
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  • Probabilistic dynamic epistemic logic.Barteld P. Kooi - 2003 - Journal of Logic, Language and Information 12 (4):381-408.
    In this paper I combine the dynamic epistemic logic ofGerbrandy (1999) with the probabilistic logic of Fagin and Halpern (1994). The resultis a new probabilistic dynamic epistemic logic, a logic for reasoning aboutprobability, information, and information change that takes higher orderinformation into account. Probabilistic epistemic models are defined, and away to build them for applications is given. Semantics and a proof systemis presented and a number of examples are discussed, including the MontyHall Dilemma.
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  • Epistemic planning for single- and multi-agent systems.Thomas Bolander & Mikkel Birkegaard Andersen - 2011 - Journal of Applied Non-Classical Logics 21 (1):9-34.
    In this paper, we investigate the use of event models for automated planning. Event models are the action defining structures used to define a semantics for dynamic epistemic logic. Using event models, two issues in planning can be addressed: Partial observability of the environment and knowledge. In planning, partial observability gives rise to an uncertainty about the world. For single-agent domains, this uncertainty can come from incomplete knowledge of the starting situation and from the nondeterminism of actions. In multi-agent domains, (...)
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  • Conformant plans and beyond: Principles and complexity.Blai Bonet - 2010 - Artificial Intelligence 174 (3-4):245-269.
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  • Sequential Monte Carlo in reachability heuristics for probabilistic planning.Daniel Bryce, Subbarao Kambhampati & David E. Smith - 2008 - Artificial Intelligence 172 (6-7):685-715.
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  • Knowledge, action, and the frame problem.Richard B. Scherl & Hector J. Levesque - 2003 - Artificial Intelligence 144 (1-2):1-39.
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  • Planning and acting in partially observable stochastic domains.Leslie Pack Kaelbling, Michael L. Littman & Anthony R. Cassandra - 1998 - Artificial Intelligence 101 (1-2):99-134.
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  • An algorithm for probabilistic planning.Nicholas Kushmerick, Steve Hanks & Daniel S. Weld - 1995 - Artificial Intelligence 76 (1-2):239-286.
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  • Dynamic Update with Probabilities.Johan Benthem, Jelle Gerbrandy & Barteld Kooi - 2009 - Studia Logica 93 (1):67-96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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