从进化生态系统模拟到人类行为的计算模型。

IF 3.2 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Peter J Bentley, Soo Ling Lim
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引用次数: 1

摘要

今天,我们有广泛可用的计算工具,可以采用更合乎道德的方法来研究人类认知和行为。我们认为,使用计算机模型来研究进化中的生态系统提供了丰富的灵感来源,因为它们使研究随时间变化的复杂系统成为可能。这些方法通常结合了遗传算法和基于主体的模型,涵盖了从游戏到复杂性的理论方法,从自我复制研究到眼睛进化的自然启发方法,以及人类进化生态系统,从整个经济到团队合作中的个性影响。这里提供的工作综述说明了进化生态系统模拟的力量,以及它们如何为研究人员提供新的见解。他们还展示了一种新颖的假设探索方法:建立一个计算模型,封装人类认知的假设,使其能够在不同条件下进行测试,并将其预测与实际数据进行比较,从而实现确证。这种人类行为的计算模型为我们提供了虚拟的测试实验室,在那里可以进行无限的实验。本文分类为:计算机科学与机器人>人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

From evolutionary ecosystem simulations to computational models of human behavior.

From evolutionary ecosystem simulations to computational models of human behavior.

We have a wide breadth of computational tools available today that enable a more ethical approach to the study of human cognition and behavior. We argue that the use of computer models to study evolving ecosystems provides a rich source of inspiration, as they enable the study of complex systems that change over time. Often employing a combination of genetic algorithms and agent-based models, these methods span theoretical approaches from games to complexification, nature-inspired methods from studies of self-replication to the evolution of eyes, and evolutionary ecosystems of humans, from entire economies to the effects of personalities in teamwork. The review of works provided here illustrates the power of evolutionary ecosystem simulations and how they enable new insights for researchers. They also demonstrate a novel methodology of hypothesis exploration: building a computational model that encapsulates a hypothesis of human cognition enables it to be tested under different conditions, with its predictions compared to real data to enable corroboration. Such computational models of human behavior provide us with virtual test labs in which unlimited experiments can be performed. This article is categorized under: Computer Science and Robotics > Artificial Intelligence.

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来源期刊
CiteScore
7.30
自引率
7.70%
发文量
50
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