Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Abstract—Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. The navigation task requires identifying safe, traversable pat...
Michael J. Procopio, Jane Mulligan, Gregory Z. Gru...
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean ...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...