3 accepted papers
We address a coordination problem for a team of heterogeneous and energy-limited agents to achieve cooperative tasks given as team-level spatio-temporal specifications. We assume that agents have stochastic energy dynamics and do not have identical capabilities. We define the team-level specificatio…
We propose an automata-theoretic approach for reinforcement learning (RL) under complex spatio-temporal constraints with time windows. The problem is formulated using a Markov decision process under a bounded temporal logic constraint. Different from existing RL methods that can eventually learn opt…
We propose a novel constrained reinforcement learning method for finding optimal policies in Markov Decision Processes while satisfying temporal logic constraints with a desired probability throughout the learning process. An automata-theoretic approach is proposed to ensure the probabilistic satisf…