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Guangyuan Wang

Research Intern - McGill University
Supervisor
Research Topics
Deep Learning
Machine Learning Theory
Reinforcement Learning

Publications

Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning
Mohammad Sami Nur Islam
Existing actor-critic algorithms, which are popular for continuous control reinforcement learning (RL) tasks, suffer from poor sample effici… (see more)ency due to lack of principled exploration mechanism within them. Motivated by the success of Thompson sampling for efficient exploration in RL, we propose a novel model-free RL algorithm, Langevin Soft Actor Critic (LSAC), which prioritizes enhancing critic learning through uncertainty estimation over policy optimization. LSAC employs three key innovations: approximate Thompson sampling through distributional Langevin Monte Carlo (LMC) based