Search Results for author: Min Cheng

Found 3 papers, 2 papers with code

Provable Policy Gradient Methods for Average-Reward Markov Potential Games

no code implementations9 Mar 2024 Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian

We prove that both algorithms based on independent policy gradient and independent natural policy gradient converge globally to a Nash equilibrium for the average reward criterion.

Policy Gradient Methods

Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation

1 code implementation NeurIPS 2023 Ruida Zhou, Tao Liu, Min Cheng, Dileep Kalathil, P. R. Kumar, Chao Tian

We study robust reinforcement learning (RL) with the goal of determining a well-performing policy that is robust against model mismatch between the training simulator and the testing environment.

reinforcement-learning Reinforcement Learning (RL)

MMED: A Multi-domain and Multi-modality Event Dataset

1 code implementation4 Apr 2019 Zhenguo Yang, Zehang Lin, Min Cheng, Qing Li, Wenyin Liu

In this work, we construct and release a multi-domain and multi-modality event dataset (MMED), containing 25, 165 textual news articles collected from hundreds of news media sites (e. g., Yahoo News, Google News, CNN News.)

Question Answering Retrieval +1

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