Agent-oriented incremental activity recognition for human teams
Conference Paper, Proceedings of 22nd International Joint Conference on Artificial Intelligence (IJCAI '11), Vol. 2, pp. 1402 - 1407, July, 2011
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.
BibTeX
@conference{Masato-2011-7334,author = {D. Masato and T. Norman and W. Vasconcelos and Katia Sycara},
title = {Agent-oriented incremental activity recognition for human teams},
booktitle = {Proceedings of 22nd International Joint Conference on Artificial Intelligence (IJCAI '11)},
year = {2011},
month = {July},
volume = {2},
pages = {1402 - 1407},
}
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