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On the Learnability of Knowledge in Multi-Agent Logics
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Since knowledge engineering is an inherently challenging and somewhat unbounded task, machine learning has been widely proposed as an alternative. In real world scenarios, we often need to explicitly model multiple agents, where intelligent agents act towards achieving goals either by coordinating with the other agents or by overseeing the opponents moves, if in a competitive context. We consider the knowledge acquisition problem where agents have knowledge about the world and other agents anddoi:10.24963/ijcai.2021/685 fatcat:z2koy36cujgwli4vht7dpifj4u