Behavior-analysis and -prediction for agents in real-time and dynamic adversarial environments

Authors:
Carsten Rachuy;Ubbo Visser
Affiliations:
Kognitve Neuroinformatik, Universität Bremen, Germany, rachuy@informatik.uni-bremen.de;Department of Computer Science, University of Miami, USA, visser@cs.miami.edu
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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Abstract

We present an approach for recognition and subsequent prediction of spatio-temporal patterns in a physical real-time environment. The motivation is to provide a domain-independent approach for the analysis of agent's behavior in adversarial multi-agent scenarios. The goal is to create an opponent-specific model, which is used for behavior prediction. We develop a framework for representing a set of hierarchically structured facts, events and actions using temporal logic. Recognition, learning, and prediction is performed using a probabilistic approach utilizing Bayesian Networks. The system is applied to the domain of the RoboCup 3D Simulation League and evaluated with regard to the recognition-, prediction-and realtime capabilities.