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  1. Answers set programs for non-transferable utility games: Expressiveness, complexity and applications.Giovanni Amendola, Gianluigi Greco & Pierfrancesco Veltri - 2022 - Artificial Intelligence 302 (C):103606.
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  • Compactly representing utility functions using weighted goals and the max aggregator.Joel Uckelman & Ulle Endriss - 2010 - Artificial Intelligence 174 (15):1222-1246.
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  • What will they say?—Public Announcement Games.Hans van Ditmarsch & Thomas Ågotnes - 2011 - Synthese 179 (S1):57 - 85.
    Dynamic epistemic logic describes the possible information-changing actions available to individual agents, and their knowledge pre-and post conditions. For example, public announcement logic describes actions in the form of public, truthful announcements. However, little research so far has considered describing and analysing rational choice between such actions, i.e., predicting what rational self-interested agents actually will or should do. Since the outcome of information exchange ultimately depends on the actions chosen by all the agents in the system, and assuming that agents (...)
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  • Johan van Benthem on Logic and Information Dynamics.Alexandru Baltag & Sonja Smets (eds.) - 2014 - Cham, Switzerland: Springer International Publishing.
    This book illustrates the program of Logical-Informational Dynamics. Rational agents exploit the information available in the world in delicate ways, adopt a wide range of epistemic attitudes, and in that process, constantly change the world itself. Logical-Informational Dynamics is about logical systems putting such activities at center stage, focusing on the events by which we acquire information and change attitudes. Its contributions show many current logics of information and change at work, often in multi-agent settings where social behavior is essential, (...)
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  • Characteristic function games with restricted agent interactions: Core-stability and coalition structures.Georgios Chalkiadakis, Gianluigi Greco & Evangelos Markakis - 2016 - Artificial Intelligence 232 (C):76-113.
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  • Coalitional games induced by matching problems: Complexity and islands of tractability for the Shapley value.Gianluigi Greco, Francesco Lupia & Francesco Scarcello - 2020 - Artificial Intelligence 278 (C):103180.
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  • Effort Games and the Price of Myopia.Yoram Bachrach, Michael Zuckerman & Jeffrey S. Rosenschein - 2009 - Mathematical Logic Quarterly 55 (4):377-396.
    We consider Effort Games, a game-theoretic model of cooperation in open environments, which is a variant of the principal-agent problem from economic theory. In our multiagent domain, a common project depends on various tasks; carrying out certain subsets of the tasks completes the project successfully, while carrying out other subsets does not. The probability of carrying out a task is higher when the agent in charge of it exerts effort, at a certain cost for that agent. A central authority, called (...)
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  • A Computational Learning Semantics for Inductive Empirical Knowledge.Kevin T. Kelly - 2014 - In Alexandru Baltag & Sonja Smets (eds.), Johan van Benthem on Logic and Information Dynamics. Cham, Switzerland: Springer International Publishing. pp. 289-337.
    This chapter presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyper-intensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidance of error in the limit and as having converged to true belief from the present time onward. Familiar topics are re-examined within (...)
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  • On the complexity of core, kernel, and bargaining set.Gianluigi Greco, Enrico Malizia, Luigi Palopoli & Francesco Scarcello - 2011 - Artificial Intelligence 175 (12-13):1877-1910.
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