Mixture of personality improved spiking actor network for efficient multi-agent cooperation
文献类型：期刊论文
| 作者 | Li, Xiyun1,3 ; Ni, Ziyi1,2; Ruan, Jingqing1,3; Meng, Linghui1,2; Shi, Jing1,2; Zhang, Tielin1,2; Xu, Bo1,2,3,4
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| 刊名 | FRONTIERS IN NEUROSCIENCE
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| 出版日期 | 2023-07-06 |
| 卷号 | 17页码:14 |
| 关键词 | multi-agent cooperation personality theory spiking actor networks multi-agent reinforcement learning theory of mind |
| DOI | 10.3389/fnins.2023.1219405 |
| 通讯作者 | Zhang, Tielin(tielin.zhang@ia.ac.cn) ; Xu, Bo(xubo@ia.ac.cn) |
| 英文摘要 | Adaptive multi-agent cooperation with especially unseen partners is becoming more challenging in multi-agent reinforcement learning (MARL) research, whereby conventional deep-learning-based algorithms suffer from the poor new-player-generalization problem, possibly caused by not considering theory-of-mind theory (ToM). Inspired by the ToM personality in cognitive psychology, where a human can easily resolve this problem by predicting others' intuitive personality first before complex actions, we propose a biologically-plausible algorithm named the mixture of personality (MoP) improved spiking actor network (SAN). The MoP module contains a determinantal point process to simulate the formation and integration of different personality types, and the SAN module contains spiking neurons for efficient reinforcement learning. The experimental results on the benchmark cooperative overcooked task showed that the proposed MoP-SAN algorithm could achieve higher performance for the paradigms with (learning) and without (generalization) unseen partners. Furthermore, ablation experiments highlighted the contribution of MoP in SAN learning, and some visualization analysis explained why the proposed algorithm is superior to some counterpart deep actor networks. |
| WOS关键词 | GO |
| WOS研究方向 | Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:001029486500001 |
| 出版者 | FRONTIERS MEDIA SA |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53705]  |
| 专题 | 复杂系统认知与决策实验室 |
| 通讯作者 | Zhang, Tielin; Xu, Bo |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Future Technol, Beijing, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Xiyun,Ni, Ziyi,Ruan, Jingqing,et al. Mixture of personality improved spiking actor network for efficient multi-agent cooperation[J]. FRONTIERS IN NEUROSCIENCE,2023,17:14. |
| APA | Li, Xiyun.,Ni, Ziyi.,Ruan, Jingqing.,Meng, Linghui.,Shi, Jing.,...&Xu, Bo.(2023).Mixture of personality improved spiking actor network for efficient multi-agent cooperation.FRONTIERS IN NEUROSCIENCE,17,14. |
| MLA | Li, Xiyun,et al."Mixture of personality improved spiking actor network for efficient multi-agent cooperation".FRONTIERS IN NEUROSCIENCE 17(2023):14. |
入库方式： OAI收割
来源：自动化研究所
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