We consider the problem of having a team of Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV) pursue a second team of evaders while concurrently building a map in a...
We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
: E-marketplaces present a business-to-business (B2B) trading environment in which firms can benefit from increased choice among trading partners, and other efficiencies gained thr...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...