We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...