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"Programming" by Teaching: Neural Network Control in the Manchester Mobile Robot
1995
IFAC Proceedings Volumes
The paper presents experiments conducted with the Manchester mobile robot FortyTwo on the application of reinforcement learning to robot control. An articial neural network, forming the core component of the controller presented here, associates incoming sensor signals with corresponding motor actions. Teaching the network is achieved by initially operating the robot under human control (i.e. the robot's behaviour is the result of training, not programming). The observed actions are used to
doi:10.1016/s1474-6670(17)46985-0
fatcat:frhww5zs7jatheljogt6tp724a