Tacit Commitments Emergence in Multi-agent Reinforcement Learning | |
Liu BY(刘博寅)2,3; Zhiqiang Pu2,3; Junlong Gao1; Jianqiang Yi2,3; Zhenyu Guo1 | |
2023 | |
会议日期 | 2023-7 |
会议地点 | New Delhi, India |
英文摘要 | Tacit commitments have been widely seen as a crucial underpinning for real-world cooperation. Similarly, it could also be a key to multi-agent cooperation. This paper proposes a novel tacit commitment emergence multi-agent reinforcement learning (MARL) framework (TCEM). In MARL, we define commitment as the unique state that the agent will exhibit through its action. TCEM first equips each agent with a commitment inference module (CIM) to infer its neighbor's commitments. Then, TCEM proposes that commitments influence intrinsic motivation (CIR) to encourage agents to have casual influence on others' actions. Finally, commitment acceptance intrinsic (CAI) motivation is constructed to guide the agent in behaving considering neighbors' commitments. CIR and CAI calculate intrinsic reward using counterfactual reasoning deriving from causal inference. Empirical results show that our method can effectively improve learning performance and deliver better cooperation among agents, which helps our method show superior performance on the Google Research Football benchmark. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/58541] ![]() |
专题 | 复杂系统认知与决策实验室_群体决策智能团队 |
作者单位 | 1.Alibaba Group, Hangzhou, China 2.Institute of Automation, Chinese Academy of Sciences 3.School of Artificial Intelligence, University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Liu BY,Zhiqiang Pu,Junlong Gao,et al. Tacit Commitments Emergence in Multi-agent Reinforcement Learning[C]. 见:. New Delhi, India. 2023-7. |
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