TitleContinuous Explanation Generation in a Multi-Agent Domain
Publication TypeConference Proceedings
Year of Conference2015
AuthorsMolineaux, M, Aha, DW
Conference NameThird Annual Conference on Advances in Cognitive Systems
Date PublishedMay 2015
Conference LocationAtlanta, Georgia

An agent operating in a dynamic, multi-agent environment with partial observability should continuously generate and maintain an explanation of its observations that describes what is occurring around it. We update our existing formal model of occurrence-based explanations to describe ambiguous explanations and the actions of other agents. We also introduce a new version of DiscoverHistory, an algorithm that continuously maintains such explanations as new observations are received. In our empirical study this version of DiscoverHistory outperformed a competitor in terms of efficiency while maintaining correctness (i.e., precision and recall).

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