使用分布式认知系统和进化策略构建认知双胞胎

IF 2.1 3区心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Cognitive Systems Research Pub Date : 2025-01-20 DOI:10.1016/j.cogsys.2025.101326

Wandemberg Gibaut, Ricardo Gudwin

{"title":"使用分布式认知系统和进化策略构建认知双胞胎","authors":"Wandemberg Gibaut, Ricardo Gudwin","doi":"10.1016/j.cogsys.2025.101326","DOIUrl":null,"url":null,"abstract":"<div><div>This work presents a technique to build interaction-based Cognitive Twins (a computational version of an external agent) using input–output training and an Evolution Strategy on top of a framework for distributed Cognitive Architectures. Here, we show that it is possible to orchestrate many simple physical and virtual devices to achieve good approximations of a person’s interaction behavior by training the system in an end-to-end fashion and present performance metrics. The generated Cognitive Twin may later be used to automate tasks, generate more realistic human-like artificial agents or further investigate its behaviors.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"90 ","pages":"Article 101326"},"PeriodicalIF":2.1000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building a Cognitive Twin using a distributed cognitive system and an evolution strategy\",\"authors\":\"Wandemberg Gibaut, Ricardo Gudwin\",\"doi\":\"10.1016/j.cogsys.2025.101326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This work presents a technique to build interaction-based Cognitive Twins (a computational version of an external agent) using input–output training and an Evolution Strategy on top of a framework for distributed Cognitive Architectures. Here, we show that it is possible to orchestrate many simple physical and virtual devices to achieve good approximations of a person’s interaction behavior by training the system in an end-to-end fashion and present performance metrics. The generated Cognitive Twin may later be used to automate tasks, generate more realistic human-like artificial agents or further investigate its behaviors.</div></div>\",\"PeriodicalId\":55242,\"journal\":{\"name\":\"Cognitive Systems Research\",\"volume\":\"90 \",\"pages\":\"Article 101326\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Systems Research\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1389041725000063\",\"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/S1389041725000063","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}

引用次数: 0

摘要

这项工作提出了一种技术来构建基于交互的认知双胞胎（外部代理的计算版本），使用输入输出训练和分布式认知架构框架之上的进化策略。在这里，我们展示了可以编排许多简单的物理和虚拟设备，通过以端到端方式训练系统并提供性能指标来实现对人的交互行为的良好近似。生成的“认知双胞胎”以后可能被用于自动化任务，生成更逼真的类人人工代理，或进一步研究其行为。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Building a Cognitive Twin using a distributed cognitive system and an evolution strategy

This work presents a technique to build interaction-based Cognitive Twins (a computational version of an external agent) using input–output training and an Evolution Strategy on top of a framework for distributed Cognitive Architectures. Here, we show that it is possible to orchestrate many simple physical and virtual devices to achieve good approximations of a person’s interaction behavior by training the system in an end-to-end fashion and present performance metrics. The generated Cognitive Twin may later be used to automate tasks, generate more realistic human-like artificial agents or further investigate its behaviors.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

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

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.