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Bayesian Agent Adaptation in Complex Dynamic Systems Vu, T., Powers, R., & Shoham, Y. (2006). Learning against multiple opponents. In Proceedings of the fifth international joint conference on autonomous agents and multiagent systems (pp. 752759). New York: ACM. Wang, F. (2002). Self-organising communities formed by middle agents. In Proceedings of the first international joint conference on autonomous agents and multiagent systems (pp. 1333-1339). New York: ACM Press. Welch, G., & Bishop, G. (1995). An introduction to the Kalman filter (Tech. Rep.). Chapel Hill, NC: University of North Carolina at Chapel Hill. Wooldridge, M. (2002). An introduction to multi-agent systems. Wiley. key terMs and defInItIons Agent: An agent receives input from the environment through its sensors and interacts with the environment to try and achieve some goal. Bayesian probability: is an interpretation of probability which describes probability as a "personal belief", based on combining any prior with observed information. Bayes' rule: Bayes' rule is the equation specifying how to update beliefs about the world, given new