3 papers
cs.LG2025
RLAF: Reinforcement Learning from Automaton Feedback
Mahyar Alinejad, Alvaro Velasquez, Yue Wang +1
Reinforcement Learning (RL) in environments with complex, history-dependent reward structures poses significant challenges for traditional methods. In this work, we introduce a nov…
cs.LG2024
Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards
Noah Topper, Alvaro Velasquez, George Atia
Inverse reinforcement learning (IRL) is the problem of inferring a reward function from expert behavior. There are several approaches to IRL, but most are designed to learn a Marko…
cs.LG2023
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning
Suraj Singireddy, Precious Nwaorgu, Andre Beckus +5
Reinforcement learning (RL) is a powerful tool for finding optimal policies in sequential decision processes. However, deep RL methods have two weaknesses: collecting the amount of…