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In this talk I present recent work on combining game theory, statistics, and control theory. This combination provides new techniques for predicting / controlling any system comprising humans, human groups (e.g., firms, tribes), and / or adaptive automated systems (e.g., reinforcement learning robots). As illustrations, I will focus on three projects: 1) Suppressing flutter in an airplane wing by controlling a set of autonomous micro-flaps at its trailing edge. 2) Predicting the behavior of an interacting attacker and defender of a cyber-physical system, to enable improved design of such systems. 3) First raising taxes in a human economy, and then lowering them back to the starting values, to steer the economy to a Pareto superior equilibrium. Host: Garrett Kenyon, gkenyon@lanl.gov, 7-1900, IS & T |