6 citations · 18 across the 16 of their papers we have counts for
5 papers · 1 filter
Omega-Regular Decision Processes
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
Regular decision processes (RDPs) are a subclass of non-Markovian decision processes where the transition and reward functions are guarded by some regular property of the past (a l…
Policy Synthesis and Reinforcement Learning for Discounted LTL
Rajeev Alur, Osbert Bastani, Kishor Jothimurugan +3
The difficulty of manually specifying reward functions has led to an interest in using linear temporal logic (LTL) to express objectives for reinforcement learning (RL). However, L…
Reward Shaping for Reinforcement Learning with Omega-Regular Objectives
E. M. Hahn, M. Perez, S. Schewe +3
Recently, successful approaches have been made to exploit good-for-MDPs automata (Büchi automata with a restricted form of nondeterminism) for model free reinforcement learning, a…
Omega-Regular Objectives in Model-Free Reinforcement Learning
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
We provide the first solution for model-free reinforcement learning of ω-regular objectives for Markov decision processes (MDPs). We present a constructive reduction from the almos…
The Reach-Avoid Problem for Constant-Rate Multi-Mode Systems
Shankara Narayanan Krishna, Aviral Kumar, Fabio Somenzi +2
A constant-rate multi-mode system is a hybrid system that can switch freely among a finite set of modes, and whose dynamics is specified by a finite number of real-valued variables…