Sophie C.F. Hendrikse , Jan Treur , Sander L. Koole
{"title":"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","authors":"Sophie C.F. Hendrikse , Jan Treur , Sander L. Koole","doi":"10.1016/j.cogsys.2023.101182","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"84 ","pages":"Article 101182"},"PeriodicalIF":2.1000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S138904172300116X/pdfft?md5=08091b812cf5784f11b2664d81cfcecb&pid=1-s2.0-S138904172300116X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Relationship-specific and relationship-independent behavioural adaptivity in affiliation and bonding: A multi-adaptive dynamical systems approach\",\"authors\":\"Sophie C.F. Hendrikse , Jan Treur , Sander L. Koole\",\"doi\":\"10.1016/j.cogsys.2023.101182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":55242,\"journal\":{\"name\":\"Cognitive Systems Research\",\"volume\":\"84 \",\"pages\":\"Article 101182\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S138904172300116X/pdfft?md5=08091b812cf5784f11b2664d81cfcecb&pid=1-s2.0-S138904172300116X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Systems Research\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S138904172300116X\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S138904172300116X","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.
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.