David Lotspeich

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This paper describes work in progress on a neural-based reinforcement learning architecture for the design of reactive control policies for an autonomous robot. Reinforcement learning techniques allow a programmer to specify the control program at the level of the desired behavior of the robot, rather than at the level of the program that generates the(More)
Within the field of robotics, much recent attention has been given to control techniques that have been termed reactive or behavior-based. The design of such control systems for even a remotely interesting task is typically a laborious effort, requiring many hours of experimental "tweaking" as the actual behavior of the system is observed by the system(More)
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