Search Results for author: Songtao Feng

Found 4 papers, 0 papers with code

Offline Multitask Representation Learning for Reinforcement Learning

no code implementations18 Mar 2024 Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

We study offline multitask representation learning in reinforcement learning (RL), where a learner is provided with an offline dataset from different tasks that share a common representation and is asked to learn the shared representation.

reinforcement-learning Reinforcement Learning +2

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

no code implementations17 Aug 2023 Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang

In this work, we propose a model-free stage-based Q-learning algorithm and show that it achieves the same sample complexity as the best model-based algorithm, and hence for the first time demonstrate that model-free algorithms can enjoy the same optimality in the $H$ dependence as model-based algorithms.

Multi-agent Reinforcement Learning Q-Learning +1

Non-stationary Reinforcement Learning under General Function Approximation

no code implementations1 Jun 2023 Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang

To the best of our knowledge, this is the first dynamic regret analysis in non-stationary MDPs with general function approximation.

reinforcement-learning Reinforcement Learning +1

Provable Benefit of Multitask Representation Learning in Reinforcement Learning

no code implementations13 Jun 2022 Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang

To the best of our knowledge, this is the first theoretical study that characterizes the benefit of representation learning in exploration-based reward-free multitask RL for both upstream and downstream tasks.

Offline RL reinforcement-learning +3

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