Interpretation and Processing of Position Data for the Empirical Study of the Behavior of Simulation League RoboCup Teams
نویسندگان
چکیده
One of the key problems in the study of multiagent systems in which the agents exhibit continuous behavior is the automatic recognition and analysis of intentional activities based on observable behavior. Such an automated analysis requires software systems to structure continuous motions into episodes that are meaningful in the respective application domain, to acquire and maintain models of agent activities, and to use such models to reason about multiagent system behavior. In this paper we describe the application of automatic interpretation methods to the empirical study of the playing behavior of teams in the RoboCup simulation league based on motion and episode models.
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