【二】最新多智能体强化学习文章如何查阅{顶会:AAAI、 ICML }
相关文章:
【二】最新多智能体强化学习文章如何查阅{顶会:AAAI、 ICML }
【三】多智能体强化学习(MARL)近年研究概览 {Analysis of emergent behaviors(行为分析)_、Learning communication(通信学习)}
【四】多智能体强化学习(MARL)近年研究概览 {Learning cooperation(协作学习)、Agents modeling agents(智能体建模)}
1.中国计算机学会(CCF)推荐国际学术会议和期刊目录
CCF推荐国际学术会议(参考链接:链接点击查阅具体分类)
类别如下计算机系统与高性能计算,计算机网络,网络与信息安全,软件工程,系统软件与程序设计语言,数据库、数据挖掘与内容检索,计算机科学理论,计算机图形学与多媒体,人工智能与模式识别,人机交互与普适计算,前沿、交叉与综合
2021 ICML 多智能体强化学习论文整理汇总
| 类别名称 | 数量 |
|---|---|
| 投稿量 | 5513 |
| 接收量 | 1184 |
| 强化学习方向文章 | 163 |
| 其中多智能体强化学习文章 | 15 |
ICML地位:
1.1 中国计算机学会推荐国际学术会议
(人工智能与模式识别)
1.1.1 A类
|
序号 |
会议简称 |
会议全称 |
出版社 |
网址 |
|
1 |
AAAI |
AAAI Conference on Artificial Intelligence |
AAAI |
|
|
2 |
CVPR |
IEEE Conference on Computer Vision and |
IEEE |
|
|
3 |
ICCV |
International Conference on Computer |
IEEE |
|
|
4 |
ICML |
International Conference on Machine |
ACM |
|
|
5 |
IJCAI |
International Joint Conference on Artificial |
Morgan Kaufmann |
1.1.2 B类
|
序号 |
会议简称 |
会议全称 |
出版社 |
网址 |
|
1 |
COLT |
Annual Conference on Computational |
Springer |
|
|
2 |
NIPS |
Annual Conference on Neural Information |
MIT Press |
1.1.3 B、C类更多见附录
2.推荐深度强化学习实验室及链接
2.1 arXiv
arXiv是一个免费的分发服务和开放存取的档案,收录了物理、数学、计算机科学、定量生物学、定量金融、统计学、电气工程和系统科学以及经济学等领域的1,917,177篇学术文章。本网站上的材料没有经过arXiv的同行评审。

2.2 深度强化学习实验室
DeepRL——github:https://github.com/neurondance
微信公众号:Deep-RL
官网:http://www.neurondance.com/

论坛:http://deeprl.neurondance.com/

2.3 AI 会议Deadlines

2.4 ICML官网:

3.最新多智能体强化学习方向论文
3.1 ICML International Conference on Machine Learning
[1]. Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
作者: Shariq Iqbal (University of Southern California) · Christian Schroeder (University of Oxford) · Bei Peng (University of Oxford) · Wendelin Boehmer (Delft University of Technology) · Shimon Whiteson (University of Oxford) · Fei Sha (Google Research)
[2]. UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
作者: Tarun Gupta (University of Oxford) · Anuj Mahajan (Dept. of Computer Science, University of Oxford) · Bei Peng (University of Oxford) · Wendelin Boehmer (Delft University of Technology) · Shimon Whiteson (University of Oxford)
[3]. Emergent Social Learning via Multi-agent Reinforcement Learning
作者: Kamal Ndousse (OpenAI) · Douglas Eck (Google Brain) · Sergey Levine (UC Berkeley) · Natasha Jaques (Google Brain, UC Berkeley)
[4]. DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
作者: Wei-Fang Sun (National Tsing Hua University) · Cheng-Kuang Lee (NVIDIA Corporation) · Chun-Yi Lee (National Tsing Hua University)
[5]. Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
作者: Iou-Jen Liu (University of Illinois at Urbana-Champaign) · Unnat Jain (UIUC) · Raymond Yeh (University of Illinois at Urbana–Champaign) · Alexander Schwing (UIUC)
[6]. Large-Scale Multi-Agent Deep FBSDEs
作者: Tianrong Chen (Georgia Institute of Technology) · Ziyi Wang (Georgia Institute of Technology) · Ioannis Exarchos (Stanford University) · Evangelos Theodorou (Georgia Tech)
[7]. Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
作者: Anuj Mahajan (Dept. of Computer Science, University of Oxford) · Mikayel Samvelyan (University College London) · Lei Mao (NVIDIA) · Viktor Makoviychuk (NVIDIA) · Animesh Garg (University of Toronto, Vector Institute, Nvidia) · Jean Kossaifi (NVIDIA) · Shimon Whiteson (University of Oxford) · Yuke Zhu (University of Texas - Austin) · Anima Anandkumar (Caltech and NVIDIA)
[8]. Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
作者: Filippos Christianos (University of Edinburgh) · Georgios Papoudakis (The University of Edinburgh) · Muhammad Arrasy Rahman (The University of Edinburgh) · Stefano Albrecht (University of Edinburgh)
[9]. Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
作者: Tung-Che Liang (Duke University) · Jin Zhou (Duke University) · Yun-Sheng Chan (National Chiao Tung University) · Tsung-Yi Ho (National Tsing Hua University) · Krishnendu Chakrabarty (Duke University) · Cy Lee (National Chiao Tung University)
[10]. A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
作者: Dong Ki Kim (MIT) · Miao Liu (IBM) · Matthew Riemer (IBM Research) · Chuangchuang Sun (MIT) · Marwa Abdulhai (MIT) · Golnaz Habibi (MIT) · Sebastian Lopez-Cot (MIT) · Gerald Tesauro (IBM Research) · Jonathan How (MIT)
[11]. Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
作者: Joel Z Leibo (DeepMind) · Edgar Duenez-Guzman (DeepMind) · Alexander Vezhnevets (DeepMind) · John Agapiou (DeepMind) · Peter Sunehag () · Raphael Koster (DeepMind) · Jayd Matyas (DeepMind) · Charles Beattie (DeepMind Technologies Limited) · Igor Mordatch (Google Brain) · Thore Graepel (DeepMind)
[12]. Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
作者: Luke Marris (DeepMind) · Paul Muller (DeepMind) · Marc Lanctot (DeepMind) · Karl Tuyls (DeepMind) · Thore Graepel (DeepMind)
[13]. Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
作者: Bo Liu (University of Texas, Austin) · Qiang Liu (UT Austin) · Peter Stone (University of Texas at Austin) · Animesh Garg (University of Toronto, Vector Institute, Nvidia) · Yuke Zhu (University of Texas - Austin) · Anima Anandkumar (California Institute of Technology)
[14]. Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
作者: Matthieu Zimmer (Shanghai Jiao Tong University) · Claire Glanois (Shanghai Jiao Tong University) · Umer Siddique (Shanghai Jiao Tong University) · Paul Weng (Shanghai Jiao Tong University)
[15]. FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning
作者: Tianhao Zhang (Peking University) · yueheng li (Peking university) · Chen Wang (Peking University) · Zongqing Lu (Peking University) · Guangming Xie (1. State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University; 2. Institute of Ocean Research, Peking University)
3.2 AAAI Conference on Artificial Intelligence
会议时间节点
- August 15 – August 30, 2020: Authors register on the AAAI web site
- September 1, 2020: Electronic abstracts due at 11:59 PM UTC-12 (anywhere on earth)
- September 9, 2020: Electronic papers due at 11:59 PM UTC-12 (anywhere on earth)
- September 29, 2020: Abstracts AND full papers due for revisions of rejected NeurIPS/EMNLP submissions by 11:59 PM UTC-12 (anywhere on earth)
- AAAI-21 Reviewing Process: Two-Phase Reviewing and NeurIPS/EMNLP Fast Track Submissions
- November 3-5, 2020: Author Feedback Window (anywhere on earth)
- December 1, 2020: Notification of acceptance or rejection
具体论文见链接:http://deeprl.neurondance.com/d/191-82aaai2021
接收论文列表(共84篇)
4.附录
4.1 B类
|
序号 |
会议简称 |
会议全称 |
出版社 |
网址 |
|
1 |
COLT |
Annual Conference on Computational |
Springer |
|
|
2 |
NIPS |
Annual Conference on Neural Information |
MIT Press |
|
|
3 |
ACL |
Annual Meeting of the Association for |
ACL |
|
|
4 |
EMNLP |
Conference on Empirical Methods in Natural |
ACL |
|
|
5 |
ECAI |
European Conference on Artificial |
IOS Press |
|
|
6 |
ECCV |
European Conference on Computer Vision |
Springer |
|
|
7 |
ICRA |
IEEE International Conference on Robotics |
IEEE |
|
|
8 |
ICAPS |
International Conference on Automated |
AAAI |
|
|
9 |
ICCBR |
International Conference on Case-Based |
Springer |
|
|
10 |
COLING |
International Conference on Computational |
ACM |
|
|
11 |
KR |
International Conference on Principles of |
Morgan Kaufmann |
|
|
12 |
UAI |
International Conference on Uncertainty |
AUAI |
|
|
13 |
AAMAS |
International Joint Conference |
Springer |
4.2 C类
|
序号 |
会议简称 |
会议全称 |
出版社 |
网址 |
|
1 |
ACCV |
Asian Conference on Computer Vision |
Springer |
|
|
2 |
CoNLL |
Conference on Natural Language Learning |
CoNLL |
|
|
3 |
GECCO |
Genetic and Evolutionary Computation |
ACM |
|
|
4 |
ICTAI |
IEEE International Conference on Tools with |
IEEE |
|
|
5 |
ALT |
International Conference on Algorithmic |
Springer |
|
|
6 |
ICANN |
International Conference on Artificial Neural |
Springer |
|
|
7 |
FGR |
International Conference on Automatic Face |
IEEE |
|
|
8 |
ICDAR |
International Conference on Document |
IEEE |
|
|
9 |
ILP |
International Conference on Inductive Logic |
Springer |
|
|
10 |
KSEM |
International conference on Knowledge |
Springer |
|
|
11 |
ICONIP |
International Conference on Neural |
Springer |
|
|
12 |
ICPR |
International Conference on Pattern |
IEEE |
|
|
13 |
ICB |
International Joint Conference on Biometrics |
IEEE |
|
|
14 |
IJCNN |
International Joint Conference on Neural |
IEEE |
|
|
15 |
PRICAI |
Pacific Rim International Conference on |
Springer |
|
|
16 |
NAACL |
The Annual Conference of the North |
NAACL |
|
|
17 |
BMVC |
British Machine Vision Conference |
British Machine |
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