隶属关系和结合中关系特异性和关系独立的行为适应性:一种多适应动力系统方法

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sophie C.F. Hendrikse , Jan Treur , Sander L. Koole
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引用次数: 0

摘要

人类在互动时经常调整自己的行为。从神经科学的角度来看,这种适应性可能涉及基于相关心理或神经网络中的适应性连接(突触可塑性)和适应性兴奋性阈值(非突触可塑性)的机制。然而,哪些适应类型是特定于一种关系的,哪些适应类型是更普遍的,这一问题往往没有得到解决。我们关注社会互动中关系特异性适应和关系独立性适应之间的区别。我们通过计算分析了在社会互动的因果途径中,适应性关系特异性和关系独立机制的相互作用是如何发生的。作为其中的一部分,我们还涵盖了这些类型的适应(适应速度和适应强度)的上下文敏感控制,有时被称为高阶适应或元可塑性。该模型通过许多探索运行来评估,其中在一组四个代理中,每个代理随机地与其他三个代理中的一个交互。对(随机)模拟结果的分析结果表明,适应对社会互动程度有很强的依赖性:更多的社会互动导致更多的互动行为的适应。这对短期和长期的一阶适应和长期的二阶适应都成立。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relationship-specific and relationship-independent behavioural adaptivity in affiliation and bonding: A multi-adaptive dynamical systems approach

Humans often adapt their behaviour toward each other when they interact. From a neuroscientific perspective, such adaptivity can involve mechanisms based on adaptive connections (synaptic plasticity) and adaptive excitability thresholds (nonsynaptic plasticity) within the mental or neural network concerned. It is, however, often left unaddressed which of the types of adaptation are specific for the relationship and which are more general for multiple relationships. We focus on this differentiation between relationship-specific and relationship-independent adaptation in social interactions. We analysed computationally how an interplay of adaptive relation-specific and relation-independent mechanisms occurs within the causal pathways for social interaction. As part of this, we cover also the context-sensitive control of these types of adaptation (adaptive speeds and strengths of adaptation), which is sometimes termed higher-order adaptation or metaplasticity. The model was evaluated by a number of explored runs where within a group of four agents each agent randomly has episodes of interaction with one of the three other agents. The outcomes of the analysis of the (stochastic) simulation results show a strong dependence of adaptation on the extent of social interaction: more social interaction leads to more adaptation of the interaction behaviour. This holds both for the short-term and long-term first-order adaptation and for the second-order adaptation, which is long-term.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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