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Titlebook: Games, Norms and Reasons; Logic at the Crossro Johan van Benthem,Amitabha Gupta,Eric Pacuit Book 2011 Springer Science+Business Media B.V.

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书目名称Games, Norms and Reasons
副标题Logic at the Crossro
编辑Johan van Benthem,Amitabha Gupta,Eric Pacuit
视频video
概述First-rate papers by a remarkable group of internationally prominent authors interacting with their Indian colleagues and upcoming young researchers worldwide.Highlights emerging research programmes a
丛书名称Synthese Library
图书封面Titlebook: Games, Norms and Reasons; Logic at the Crossro Johan van Benthem,Amitabha Gupta,Eric Pacuit Book 2011 Springer Science+Business Media B.V.
描述.Games, Norms, and Reasons: Logic at the Crossroads. provides an overview of modern logic focusing on its relationships with other disciplines, including new interfaces with rational choice theory, epistemology, game theory and informatics. This book continues a series called "Logic at the Crossroads" whose title reflects a view that the deep insights from the classical phase of mathematical logic can form a harmonious mixture with a new, more ambitious research agenda of understanding and enhancing human reasoning and intelligent interaction. The editors have gathered together articles from active authors in this new area that explore dynamic logical aspects of norms, reasons, preferences and beliefs in human agency, human interaction and groups. The book pays a special tribute to Professor Rohit Parikh, a pioneer in this movement.
出版日期Book 2011
关键词Dynamic Doxastic Logic; Dynamic Epistemic Logic; Epistemic Logic; Justification Logic; Modal Logic; Prefe
版次1
doihttps://doi.org/10.1007/978-94-007-0714-6
isbn_softcover978-94-007-3577-4
isbn_ebook978-94-007-0714-6Series ISSN 0166-6991 Series E-ISSN 2542-8292
issn_series 0166-6991
copyrightSpringer Science+Business Media B.V. 2011
The information of publication is updating

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Games, Norms and Reasons978-94-007-0714-6Series ISSN 0166-6991 Series E-ISSN 2542-8292
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https://doi.org/10.1007/978-3-540-74358-3outcome, which is jointly determined by all the agents’ choices, assigns a reward to each agent. A learning algorithm is a mapping from a history of past actions, outcomes, and rewards to a current choice of action. Our goal is to characterize the dynamics of multiple agents playing according to no-regret learning algorithms.
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https://doi.org/10.1007/978-3-662-66247-2purpose of communications is (typically) to create such an update of knowledge in the recipient. However, there is often a lack of concordance between the intended update and that which occurs, leading to interesting situations and much work for knowledge theorists
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Why Meanings Are Not Normative,y following the publication of Kripke’s book on Wittgenstein’s discussion of rule-following. It will present an argument to put into doubt what is a fairly widespread assumption about the normative nature of linguistic meaning by looking at the relation that linguistic meaning bears to an agent’s linguistic intentions.
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Modal Logic for Lexicographic Preference Aggregation,ctatorial aggregation procedure satisfying desirable properties. More recently, research in judgment aggregation has produced a plethora of analogous results pertaining to judgments (cf., [5, 9, 10]). One may get the impression, from this series of results, that it is hopeless to look for a systematic and satisfying aggregation procedure.
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