Abstract
Boolean games offer a compact alternative to normal-form games, by encoding the goal of each agent as a propositional formula. In this paper, we show how this framework can be naturally extended to model situations in which agents are uncertain about other agents’ goals. We first use uncertainty measures from possibility theory to semantically define (solution concepts to) Boolean games with incomplete information. Then we present a syntactic characterization of these semantics, which can readily be implemented, and we characterize the computational complexity.
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De Clercq, S., Schockaert, S., De Cock, M., Nowé, A. (2014). Possibilistic Boolean Games: Strategic Reasoning under Incomplete Information. In: Fermé, E., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2014. Lecture Notes in Computer Science(), vol 8761. Springer, Cham. https://doi.org/10.1007/978-3-319-11558-0_14
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DOI: https://doi.org/10.1007/978-3-319-11558-0_14
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