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Jiechuan Jiang
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2020 – today
- 2024
- [c13]Kefan Su, Siyuan Zhou, Jiechuan Jiang, Chuang Gan, Xiangjun Wang, Zongqing Lu:
Multi-Agent Alternate Q-Learning. AAMAS 2024: 1791-1799 - [i13]Jiechuan Jiang, Kefan Su, Zongqing Lu:
Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey. CoRR abs/2401.04934 (2024) - [i12]Weihao Tan, Ziluo Ding, Wentao Zhang, Boyu Li, Bohan Zhou, Junpeng Yue, Haochong Xia, Jiechuan Jiang, Longtao Zheng, Xinrun Xu, Yifei Bi, Pengjie Gu, Xinrun Wang, Börje F. Karlsson
, Bo An, Zongqing Lu:
Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study. CoRR abs/2403.03186 (2024) - [i11]Xinrun Xu, Yuxin Wang, Chaoyi Xu, Ziluo Ding, Jiechuan Jiang, Zhiming Ding, Börje F. Karlsson:
A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges. CoRR abs/2403.10249 (2024) - 2023
- [c12]Jiechuan Jiang, Zongqing Lu:
Online Tuning for Offline Decentralized Multi-Agent Reinforcement Learning. AAAI 2023: 8050-8059 - [c11]Jiechuan Jiang, Zongqing Lu:
Adaptive Learning Rates for Multi-Agent Reinforcement Learning. AAMAS 2023: 23-30 - [c10]Jiechuan Jiang, Zongqing Lu:
Offline Decentralized Multi-Agent Reinforcement Learning. ECAI 2023: 1148-1155 - [c9]Bohan Zhou, Ke Li, Jiechuan Jiang, Zongqing Lu:
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer. NeurIPS 2023 - [i10]Jiechuan Jiang, Zongqing Lu:
Best Possible Q-Learning. CoRR abs/2302.01188 (2023) - [i9]Hao Luo
Model-Based Decentralized Policy Optimization. CoRR abs/2302.08139 (2023) - [i8]Bohan Zhou, Ke Li, Jiechuan Jiang, Zongqing Lu:
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer. CoRR abs/2306.12860 (2023) - 2022
- [c8]Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen McAleer, Hao Dong, Song-Chun Zhu, Yaodong Yang:
Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning. NeurIPS 2022 - [c7]Jiechuan Jiang, Zongqing Lu:
I2Q: A Fully Decentralized Q-Learning Algorithm. NeurIPS 2022 - [c6]Xiaopeng Yu, Jiechuan Jiang, Wanpeng Zhang, Haobin Jiang, Zongqing Lu:
Model-Based Opponent Modeling. NeurIPS 2022 - 2021
- [c5]Jiechuan Jiang, Zongqing Lu:
The Emergence of Individuality. ICML 2021: 4992-5001 - [i7]Jiechuan Jiang, Zongqing Lu:
Offline Decentralized Multi-Agent Reinforcement Learning. CoRR abs/2108.01832 (2021) - [i6]Xiaopeng Yu, Jiechuan Jiang, Haobin Jiang, Zongqing Lu:
Model-Based Opponent Modeling. CoRR abs/2108.01843 (2021) - 2020
- [c4]Jiechuan Jiang, Zongqing Lu:
Generative Exploration and Exploitation. AAAI 2020: 4337-4344 - [c3]Jiechuan Jiang, Chen Dun, Tiejun Huang, Zongqing Lu:
Graph Convolutional Reinforcement Learning. ICLR 2020 - [i5]Jiechuan Jiang, Zongqing Lu:
The Emergence of Individuality in Multi-Agent Reinforcement Learning. CoRR abs/2006.05842 (2020)
2010 – 2019
- 2019
- [c2]Jiechuan Jiang, Zongqing Lu:
Learning Fairness in Multi-Agent Systems. NeurIPS 2019: 13854-13865 - [i4]Jiechuan Jiang, Zongqing Lu:
Generative Exploration and Exploitation. CoRR abs/1904.09605 (2019) - [i3]Jiechuan Jiang, Zongqing Lu:
Learning Fairness in Multi-Agent Systems. CoRR abs/1910.14472 (2019) - 2018
- [c1]Jiechuan Jiang, Zongqing Lu:
Learning Attentional Communication for Multi-Agent Cooperation. NeurIPS 2018: 7265-7275 - [i2]Jiechuan Jiang, Zongqing Lu:
Learning Attentional Communication for Multi-Agent Cooperation. CoRR abs/1805.07733 (2018) - [i1]Jiechuan Jiang, Chen Dun, Zongqing Lu:
Graph Convolutional Reinforcement Learning for Multi-Agent Cooperation. CoRR abs/1810.09202 (2018)
Coauthor Index
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last updated on 2024-10-02 20:41 CEST by the dblp team
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