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Computer Science > Artificial Intelligence

arXiv:2506.18920 (cs)
[Submitted on 16 Jun 2025 ]

Title: Signal Use and Emergent Cooperation

Title: 信号使用与涌现合作

Authors:Michael Williams
Abstract: In this work, we investigate how autonomous agents, organized into tribes, learn to use communication signals to coordinate their activities and enhance their collective efficiency. Using the NEC-DAC (Neurally Encoded Culture - Distributed Autonomous Communicators) system, where each agent is equipped with its own neural network for decision-making, we demonstrate how these agents develop a shared behavioral system -- akin to a culture -- through learning and signalling. Our research focuses on the self-organization of culture within these tribes of agents and how varying communication strategies impact their fitness and cooperation. By analyzing different social structures, such as authority hierarchies, we show that the culture of cooperation significantly influences the tribe's performance. Furthermore, we explore how signals not only facilitate the emergence of culture but also enable its transmission across generations of agents. Additionally, we examine the benefits of coordinating behavior and signaling within individual agents' neural networks.
Abstract: 在这项工作中,我们研究了被组织成部落的自主代理如何学习使用通信信号来协调其活动并提高集体效率。 使用NEC-DAC(神经编码文化-分布式自主通信者)系统,其中每个代理都配备了用于决策的神经网络,我们展示了这些代理如何通过学习和信号传递发展出一个共享的行为系统——类似于一种文化。 我们的研究重点是这些代理部落内部文化的自组织,以及不同的通信策略如何影响它们的适应性和合作性。 通过分析不同的社会结构,如权威等级制度,我们表明合作文化显著影响部落的表现。 此外,我们探讨了信号不仅促进文化的出现,还使其在代理的代际之间传播。 另外,我们检查了在单个代理的神经网络中协调行为和信号的好处。
Comments: 167 pages, 19 figures, PhD dissertation, UCLA, 2006
Subjects: Artificial Intelligence (cs.AI) ; Machine Learning (cs.LG); Multiagent Systems (cs.MA); Neural and Evolutionary Computing (cs.NE); Social and Information Networks (cs.SI)
Cite as: arXiv:2506.18920 [cs.AI]
  (or arXiv:2506.18920v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2506.18920
arXiv-issued DOI via DataCite

Submission history

From: Michael Williams [view email]
[v1] Mon, 16 Jun 2025 20:24:30 UTC (2,107 KB)
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