We are designing a computational architecture for a "learning economy" based on personal software agents who represent users in a virtual society and assist them in find...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
This paper explores the issues faced in creating a sys-4 tem that can learn tactical human behavior merely by observing5 a human perform the behavior in a simulation. More specific...