![]() This alternative semantics is inspired by the same quantifier alternation pattern of ∃∀ in the semantics of the know-how modality and the (monotonic) neighborhood semantics for the standard modality. (Proc IJCAI 2017:1031–1038, 2017), based on a class of Kripke neighborhood models with both the epistemic relations and neighborhood structures. In this paper, we give an alternative semantics to the non-normal logic of knowing how proposed by Fervari et al. The book can be used as the primary text for seminars on philosophical logic focused on non-normal modal logics as a supplemental text for courses on modal logic, logic in AI, or philosophical logic (either at the undergraduate or graduate level) or as the primary source for researchers interested in learning about the uses of neighborhood semantics in philosophical logic and game theory. In addition, the book discusses a broad range of topics, including standard modal logic results (i.e., completeness, decidability and definability) bisimulations for neighborhood models and other model-theoretic constructions comparisons with other semantics for modal logic (e.g., relational models, topological models, plausibility models) neighborhood semantics for first-order modal logic, applications in game theory (coalitional logic and game logic) applications in epistemic logic (logics of evidence and belief) and non-normal modal logics with dynamic modalities. In addition to presenting the relevant technical background, it highlights both the pitfalls and potential uses of neighborhood models – an interesting class of mathematical structures that were originally introduced to provide a semantics for weak systems of modal logic (the so-called non-normal modal logics). The Review of Symbolic Logic, 5(01), 122–147.This book offers a state-of-the-art introduction to the basic techniques and results of neighborhood semantics for modal logic. Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science. Annals of Mathematics and Artificial Intelligence, 42, 2004. Logical preference representation and combinatorial vote. (Ed.), Preference Change, Theory and Decision Library (Vol. Preference, priorities and belief In Grne-Yanoff, T. Mpra paper, University Library of Munich, Germany. Mentalism versus behaviourism in economics: a philosophy-of-science perspective. Where do preferences come from? Mpra paper,University Library of Munich, Germany.ĭietrich, F., & List, C. Mpra paper, University Library of Munich, Germany.ĭietrich, F., & List, C. A reason-based theory of rational choice. Proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI), (pp. In Jerôme Lang̀: compact preference representation for boolean games. ![]() 53: Cambridge University Press.īonzon, E., & Lagasquie-Schiex, M.C. Comparing apples and oranges: a randomised prospective study. We then discuss how the approach can be generalised to the multi-agent case, and allows us to reason about agents who disagree because they are motivated by different factors, and who might be able to reach consensus simply by changing their perspective.īarone, J.E. It follows that reasoning systems and algorithms developed for modal logic (with universal modality) can be employed for reasoning about reason-based preferences. The main result is a translation showing how reasoning in this logic can be captured by reasoning in a standard modal logic (KT with universal modality). In this paper we contribute to this development by developing a modal logic for reasoning about preferences that depend on a set of motivationally salient properties. The focus so far has been on modeling faculties of individual agents, such as their mood, mindset, and motivating reasons. Recent work in rational choice theory challenges this assumption, however, and aims to give more internal structure to the notion of a preference. In formal models it is usually assumed that preferences are primitive objects, and little concern is devoted to the question of how they are formed or where they come from. Preferences play a crucial role in the theory of rationality, and therefore also to computational social choice and artificial intelligence.
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