智能体群体中轮流行为的自主发展:一个计算研究

Clément Moulin-Frier, Martí Sánchez-Fibla, P. Verschure
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引用次数: 13

摘要

我们提供了一个计算模型,展示了发声代理之间的感觉运动相互作用如何自我组织轮流行为。最近的假设提出,某些灵长类物种的轮流行为源于在群体中保持声音接触的需要(例如,在密集的环境中防止视觉接触)。在这种情况下,发声可以传达关于每个群体成员存在的信息,并且轮流允许将声音信号干扰降到最低。我们认为智能体具有基于两个耦合控制回路的认知架构:一个反应性控制回路实现基本的调节行为以维持声音倾听,一个适应性控制回路学习行动策略以最大限度地提高群体成员之间的声音接触。我们表明,反应过程引导自适应学习向集体轮流策略收敛。该模型为轮替可以从与群体凝聚力和个体间声音信号干扰相关的功能约束中出现的假设提供了计算支持。我们建议未来的研究方向,以了解社会行为是如何从感觉运动相互作用中产生的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous development of turn-taking behaviors in agent populations: A computational study
We provide a computational model showing how turn-taking behaviors can self-organize out of sensorimotor interactions between vocalizing agents. Recent hypotheses propose that turn-taking behaviors in certain primate species emerge from a need to maintain vocal contact in a group (e.g. in dense environments preventing visual contact). In this context, vocalizations can convey information about the presence of each group member and taking turns allow to minimize the vocal signal interferences. We consider agents equipped with a cognitive architecture based on two coupled control loops: a reactive one implementing a basic regulatory behavior to maintain vocal listening and an adaptive one learning an action policy to maximize vocal contact among group members. We show that the reactive process bootstraps the adaptive learning to converge toward a collective turn-taking strategy. This model provides a computational support to the hypothesis that turn-taking can emerge from functional constraints related to group cohesion and inter-individual vocal signal interferences. We suggest future directions of research to understand how social behaviors can result from sensorimotor interactions.
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