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eess.SY2022
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…
eess.SY2020
Formal Controller Synthesis for Continuous-Space MDPs via Model-Free Reinforcement Learning
Abolfazl Lavaei, Fabio Somenzi, Sadegh Soudjani +2
A novel reinforcement learning scheme to synthesize policies for continuous-space Markov decision processes (MDPs) is proposed. This scheme enables one to apply model-free, off-the…