Universal artificial intelligence : sequential decisions based on algorithmic probability

Presents sequential decision theory from a novel algorithmic information theory perspective. This book introduces the two different ideas and removes the limitations by unifying them to one parameter-free theory of an optimal reinforcement learning agent embedded in an unknown environment.