Agent-Oriented Incremental Team and Activity Recognition

Masato, Daniele (University of Aberdeen) | Norman, Timothy J. (University of Aberdeen) | Vasconcelos, Wamberto W. (University of Aberdeen) | Sycara, Katia (Carnegie Mellon University)

AAAI Conferences 

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.

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