We present a powerful new account of multi-agent knowledge in the situation calculus and an effective reasoning procedure for handling knowledge queries. Our approach generalizes existing work by reifying the observations made by each agent as the world evolves, allowing for agents that are partially or completely unaware of some of the actions that have occurred. This also enables agents to reason effectively about knowledge using only their internal history of observations, rather than requiring a full history of the world. The result is a more robust and flexible account of knowledge suitable for use in partially-observable multiagent domains. Categories and Subject Descriptors I.2.4 [Artificial Intelligence]: Knowledge Representation Formalisms and Methods General Terms Theory Keywords Situation Calculus, Knowledge, Action, Observability
Ryan F. Kelly, Adrian R. Pearce