The SOSIEL Platform: Knowledge-based, cognitive, and multi-agent

Q2 Psychology

Biologically Inspired Cognitive Architectures Pub Date : 2018-10-01 DOI:10.1016/j.bica.2018.09.001

Garry Sotnik

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引用次数: 14

Abstract

This article describes the open-source cognitive multi-agent knowledge-based SOSIEL (Self-Organizing Social & Inductive Evolutionary Learning) Platform, designed for building the social components of social-ecological decision support systems, consisting of agents empowered with a cognitive architecture. The platform can simulate the cross-generational progression of one or a large number of agents that can interact among themselves and/or with coupled natural and/or technical systems, learn from their and each other’s experience, create new practices, and make decisions about taking and then take (potentially collective) actions. The platform can also be used for conducting hypothetical experiments that are focused on studying the interactions among: (a) cross-generational population dynamics, (b) self-organizing multi-layered social network structures, (c) evolving place-based knowledge, (d) learning, (e) decision-making, (f) collective action and its potential, and (g) social and (when coupled) social-ecological outcomes. The article describes a simple model that was built with the SOSIEL Platform, which simulates the co-evolution of mental models among socially learning agents.

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SOSIEL平台:基于知识、认知和多智能体

本文描述了基于开源认知多智能体知识的自组织社会(SOSIEL);归纳进化学习)平台，设计用于构建社会生态决策支持系统的社会组件，由具有认知架构的代理组成。该平台可以模拟一个或多个智能体的跨代发展，这些智能体可以在它们之间和/或与耦合的自然和/或技术系统进行交互，从它们和彼此的经验中学习，创建新的实践，并做出关于采取行动的决定，然后采取(可能是集体)行动。该平台还可用于进行假设实验，重点研究以下方面的相互作用:(a)跨代人口动态，(b)自组织多层社会网络结构，(c)不断发展的基于地点的知识，(d)学习，(e)决策，(f)集体行动及其潜力，以及(g)社会和(耦合时)社会生态结果。本文描述了一个使用SOSIEL平台构建的简单模型，该模型模拟了社会学习主体之间心理模型的共同进化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biologically Inspired Cognitive Architectures COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEN-NEUROSCIENCES

CiteScore

3.60

自引率

0.00%

发文量

期刊介绍： Announcing the merge of Biologically Inspired Cognitive Architectures with Cognitive Systems Research. 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.