A guide to completeness and complexity for modal logics of knowledge and belief
Artificial Intelligence
What can machines know?: On the properties of knowledge in distributed systems
Journal of the ACM (JACM)
Reasoning about knowledge
A logic for SDSI's linked local name spaces
Journal of Computer Security
Decidability of Hybrid Logic with Local Common Knowledge Based on Linear Temporal Logic LTL
CiE '08 Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms
Multi-agent Logics with Interacting Agents Based on Linear Temporal Logic: Deciding Algorithms
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Quantified epistemic logics for reasoning about knowledge in multi-agent systems
Artificial Intelligence
International Journal of Advanced Intelligence Paradigms
A framework to compute inference rules valid in agents' temporal logics
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Inference rules in multi-agents' temporal logics
Transactions on computational collective intelligence IV
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Decision procedure for a fragment of mutual belief logic with quantified agent variables
CLIMA'05 Proceedings of the 6th international conference on Computational Logic in Multi-Agent Systems
International Journal of Intelligent Information Technologies
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Complete axiomatizations and exponential-time decision procedures are provided for reasoning about knowledge and common knowledge when there are infinitely many agents. The results show that reasoning about knowledge and common knowledge with infinitely many agents is no harder than when there are finitely many agents, provided that we can check the cardinality of certain set differences G - G', where G and G' are sets of agents. Since our complexity results are independent of the cardinality of the sets G involved, they represent improvements over the previous results even when the sets of agents involved are finite. Moreover, our results make clear the extent to which issues of complexity and completeness depend on how the sets of agents involved are represented.