2 citations · 3 across the 3 of their papers we have counts for
4 papers
Omega-Regular Reward Machines
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
Reinforcement learning (RL) is a powerful approach for training agents to perform tasks, but designing an appropriate reward mechanism is critical to its success. However, in many…
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…
Compositional Reinforcement Learning for Discrete-Time Stochastic Control Systems
Abolfazl Lavaei, Mateo Perez, Milad Kazemi +4
We propose a compositional approach to synthesize policies for networks of continuous-space stochastic control systems with unknown dynamics using model-free reinforcement learning…
Almost-Sure Reachability in Stochastic Multi-Mode System
Fabio Somenzi, Behrouz Touri, Ashutosh Trivedi
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…