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A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents (vol 16, 753900, 2022) | |
Zhao, Zhuoya1,2![]() ![]() ![]() ![]() | |
发表期刊 | FRONTIERS IN NEUROSCIENCE
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2022-05-19 | |
卷号 | 16页码:2 |
摘要 | During dynamic social interaction, inferring and predicting others’ behaviors through theory of mind (ToM) is crucial for obtaining benefits in cooperative and competitive tasks. Current multi-agent reinforcement learning (MARL) methods primarily rely on agent observations to select behaviors, but they lack inspiration from ToM, which limits performance. In this article, we propose a multi-agent ToM decision-making (MAToMDM) model, which consists of a MAToM spiking neural network (MAToM-SNN) module and a decision-making module. We design two brain-inspired ToM modules (Self-MAToM and Other-MAToM) to predict others’ nbehaviors based on self-experience and observations of others, respectively. Each agent can adjust its behavior according to the predicted actions of others. The effectiveness of the proposed model has been demonstrated through experiments conducted in cooperative and competitive tasks. The results indicate that integrating the ToM mechanism can enhance cooperation and competition efficiency and lead to higher rewards compared with traditional MARL models. |
关键词 | brain-inspired model safety risks SNNs R-STDP theory of mind |
DOI | 10.3389/fnins.2022.920292 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Neurosciences & Neurology |
WOS类目 | Neurosciences |
WOS记录号 | WOS:000806918500001 |
出版者 | FRONTIERS MEDIA SA |
七大方向——子方向分类 | 类脑模型与计算 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49579 |
专题 | 脑图谱与类脑智能实验室_类脑认知计算 |
通讯作者 | Zeng, Yi |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Res Ctr Brain inspired Intelligence, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Future Technol, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automation, Natl Lab Pattern Recognit, Beijing, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China |
第一作者单位 | 类脑智能研究中心 |
通讯作者单位 | 类脑智能研究中心; 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Zhao, Zhuoya,Lu, Enmeng,Zhao, Feifei,et al. A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents (vol 16, 753900, 2022)[J]. FRONTIERS IN NEUROSCIENCE,2022,16:2. |
APA | Zhao, Zhuoya,Lu, Enmeng,Zhao, Feifei,Zeng, Yi,&Zhao, Yuxuan.(2022).A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents (vol 16, 753900, 2022).FRONTIERS IN NEUROSCIENCE,16,2. |
MLA | Zhao, Zhuoya,et al."A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents (vol 16, 753900, 2022)".FRONTIERS IN NEUROSCIENCE 16(2022):2. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
PIIS2666389923001265(4502KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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