Nov 12, 12:00, WeH 1302 Learning probabilistic policies for game-playing and coping with hidden state Michael Littman (Brown) This talk describes some thoughts I've had concerning a reinforcement-type learning algorithm that can converge to probabilistic policies. Possible applications include learning to win Markov games, learning in the face of hidden state, and learning in multi-agent environments.