We study the semantics of knowledge in strategic reasoning. Most existing works either implicitly assume that agents do not know one another's strategies, or that all strategies are known to all; and some works present inconsistent mixes of both features. We put forward a novel semantics for Strategy Logic with Knowledge that cleanly models whose strategies each agent knows. We study how adopting this semantics impacts agents' knowledge and strategic ability, as well as the complexity of the model-checking problem.
Reasoning About Agents That May Know Other Agents' Strategies / Belardinelli, F.; Knight, S.; Lomuscio, A.; Maubert, B.; Murano, A.; Rubin, S.. - In: IJCAI. - ISSN 1045-0823. - (2021), pp. 1787-1793. (Intervento presentato al convegno 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 nel 2021) [10.24963/ijcai.2021/246].
Reasoning About Agents That May Know Other Agents' Strategies
Maubert B.
;Murano A.
;Rubin S.
2021
Abstract
We study the semantics of knowledge in strategic reasoning. Most existing works either implicitly assume that agents do not know one another's strategies, or that all strategies are known to all; and some works present inconsistent mixes of both features. We put forward a novel semantics for Strategy Logic with Knowledge that cleanly models whose strategies each agent knows. We study how adopting this semantics impacts agents' knowledge and strategic ability, as well as the complexity of the model-checking problem.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
