Zobrazeno 1 - 10
of 6 894
pro vyhledávání: '"Cooperative agents"'
Visual navigation tasks are critical for household service robots. As these tasks become increasingly complex, effective communication and collaboration among multiple robots become imperative to ensure successful completion. In recent years, large l
Externí odkaz:
http://arxiv.org/abs/2407.00632
Akademický článek
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Autor:
Zhang, Ceyao, Yang, Kaijie, Hu, Siyi, Wang, Zihao, Li, Guanghe, Sun, Yihang, Zhang, Cheng, Zhang, Zhaowei, Liu, Anji, Zhu, Song-Chun, Chang, Xiaojun, Zhang, Junge, Yin, Feng, Liang, Yitao, Yang, Yaodong
Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely primarily on learning-based methods, whose policy generalization depe
Externí odkaz:
http://arxiv.org/abs/2308.11339
Autor:
N.J. Saam, B. Schmidt
Agent-based modelling on a computer appears to have a special role to play in the development of social science. It offers a means of discovering general and applicable social theory, and grounding it in precise assumptions and derivations, whilst ad
Standard cooperative multi-agent reinforcement learning (MARL) methods aim to find the optimal team cooperative policy to complete a task. However there may exist multiple different ways of cooperating, which usually are very needed by domain experts
Externí odkaz:
http://arxiv.org/abs/2308.14308
Autor:
Khan, Nouman, Subramanian, Vijay
The work studies the problem of decentralized constrained POMDPs in a team-setting where multiple nonstrategic agents have asymmetric information. Using an extension of Sion's Minimax theorem for functions with positive infinity and results on weak-c
Externí odkaz:
http://arxiv.org/abs/2303.14932
Learning anticipation is a reasoning paradigm in multi-agent reinforcement learning, where agents, during learning, consider the anticipated learning of other agents. There has been substantial research into the role of learning anticipation in impro
Externí odkaz:
http://arxiv.org/abs/2303.08307
Training multiple agents to perform safe and cooperative control in the complex scenarios of autonomous driving has been a challenge. For a small fleet of cars moving together, this paper proposes Lepus, a new approach to training multiple agents. Le
Externí odkaz:
http://arxiv.org/abs/2209.02157
Publikováno v:
In Information Sciences April 2023 623:220-241
