Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
A wireless system with multiple channels is considered, where each channel has several transmission states. A user learns about the instantaneous state of an available channel by ...
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
— The paper studies the coordinated path following problem, namely, steering a group of unicycles to a given path while achieving an inter-vehicle formation pattern. A novel hybr...