Proceedings

Agent-Oriented Incremental Team and Activity Recognition

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1402-1406.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-237

Abstract

Monitoring team activity is beneficial when human teams cooperate in the enactment of a joint plan. Monitoring allows teams to maintain awareness of each other's progress within the plan and it enables anticipation of information needs. Humans find this difficult, particularly in time-stressed and uncertain environments. In this paper we introduce a probabilistic model, based on Conditional Random Fields, to automatically recognise the composition of teams and the team activities in relation to a plan. The team composition and activities are recognised incrementally by interpreting a stream of spatio-temporal observations.

Daniele Masato, Timothy J. Norman, Wamberto Weber Vasconcelos, and Katia P. Sycara. 2011. Agent-Oriented Incremental Team and Activity Recognition. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1402–1406. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-237
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