Reinforcement Learning Under Probabilistic Spatio-Temporal Constraints with Time Windows
Xiaoshan Lin,Abbasali Koochakzadeh,Yasin Yazıcıoğlu,Derya Aksaray,Xiaoshan Lin,Abbasali Koochakzadeh,Yasin Yazıcıoğlu,Derya Aksaray
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 optimal policies satisfying such constraints, our proposed approach enforces a desired probability of c...
