Search Results for author: Xidong Feng

Found 16 papers, 11 papers with code

Natural Language Reinforcement Learning

no code implementations11 Feb 2024 Xidong Feng, Ziyu Wan, Mengyue Yang, Ziyan Wang, Girish A. Koushik, Yali Du, Ying Wen, Jun Wang

Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks.

Decision Making reinforcement-learning +1

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

1 code implementation29 Sep 2023 Xidong Feng, Ziyu Wan, Muning Wen, Stephen Marcus McAleer, Ying Wen, Weinan Zhang, Jun Wang

Empirical results across reasoning, planning, alignment, and decision-making tasks show that TS-LLM outperforms existing approaches and can handle trees with a depth of 64.

Decision Making Language Modelling +1

ChessGPT: Bridging Policy Learning and Language Modeling

1 code implementation NeurIPS 2023 Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, Jun Wang

Thus, we propose ChessGPT, a GPT model bridging policy learning and language modeling by integrating data from these two sources in Chess games.

Decision Making Language Modelling

Heterogeneous-Agent Reinforcement Learning

1 code implementation19 Apr 2023 Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng, Siyi Hu, Jiaming Ji, Yaodong Yang

The necessity for cooperation among intelligent machines has popularised cooperative multi-agent reinforcement learning (MARL) in AI research.

LEMMA Multi-agent Reinforcement Learning +1

Contextual Transformer for Offline Meta Reinforcement Learning

no code implementations15 Nov 2022 Runji Lin, Ye Li, Xidong Feng, Zhaowei Zhang, Xian Hong Wu Fung, Haifeng Zhang, Jun Wang, Yali Du, Yaodong Yang

Firstly, we propose prompt tuning for offline RL, where a context vector sequence is concatenated with the input to guide the conditional policy generation.

D4RL Meta Reinforcement Learning +4

TorchOpt: An Efficient Library for Differentiable Optimization

1 code implementation13 Nov 2022 Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang

TorchOpt further provides a high-performance distributed execution runtime.

Heterogeneous-Agent Mirror Learning: A Continuum of Solutions to Cooperative MARL

no code implementations2 Aug 2022 Jakub Grudzien Kuba, Xidong Feng, Shiyao Ding, Hao Dong, Jun Wang, Yaodong Yang

The necessity for cooperation among intelligent machines has popularised cooperative multi-agent reinforcement learning (MARL) in the artificial intelligence (AI) research community.

Multi-agent Reinforcement Learning

Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning

1 code implementation17 Jun 2022 Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuang Jiang, Stephen Marcus McAleer, Yiran Geng, Hao Dong, Zongqing Lu, Song-Chun Zhu, Yaodong Yang

In this study, we propose the Bimanual Dexterous Hands Benchmark (Bi-DexHands), a simulator that involves two dexterous hands with tens of bimanual manipulation tasks and thousands of target objects.

Few-Shot Learning Offline RL +2

A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning

1 code implementation31 Dec 2021 Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang

Gradient-based Meta-RL (GMRL) refers to methods that maintain two-level optimisation procedures wherein the outer-loop meta-learner guides the inner-loop gradient-based reinforcement learner to achieve fast adaptations.

Atari Games Meta Reinforcement Learning +3

Neural Auto-Curricula in Two-Player Zero-Sum Games

1 code implementation NeurIPS 2021 Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang

When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.

Multi-agent Reinforcement Learning Vocal Bursts Valence Prediction

CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation

no code implementations24 Aug 2021 Xidong Feng, Chen Chen, Dong Li, Mengchen Zhao, Jianye Hao, Jun Wang

Meta learning, especially gradient based one, can be adopted to tackle this problem by learning initial parameters of the model and thus allowing fast adaptation to a specific task from limited data examples.

Computational Efficiency Meta-Learning +1

Neural Auto-Curricula

1 code implementation4 Jun 2021 Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang

When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.

Multi-agent Reinforcement Learning

MRI Reconstruction with Interpretable Pixel-Wise Operations Using Reinforcement Learning

1 code implementation3 Apr 2020 Wentian Li, Xidong Feng, Haotian An, Xiang Yao Ng, Yu-Jin Zhang

In this work, we propose a deep reinforcement learning based method to reconstruct the corrupted images with meaningful pixel-wise operations (e. g. edge enhancing filters), so that the reconstruction process is transparent to users.

MRI Reconstruction reinforcement-learning +1

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