认知架构的时间异质性

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Carlos Johnnatan Sandoval-Arrayga, Gustavo Palacios-Ramirez, Felix Francisco Ramos-Corchado
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引用次数: 0

摘要

2020 年,麦克-法登(Mc Fadden)发表了一篇文章,讨论了算法如何在时间和空间中进行编码。通过分析大脑细胞架构的拓扑结构,认知架构可以了解人类智能在空间中发展的内在机制。在这项研究中,我们的重点是研究时间异质性作为大脑发展的一种机制,它不仅是一种生物约束,也是一种进化优势。为此,我们在虚拟环境中使用了虚拟代理,并构建了一个认知架构原型。随后,我们比较了这一认知架构在时间异质性模型和时间同质性模型下运行的利弊。在文章的最后,我们从两个角度介绍了所取得的成果。从定量的角度来看,我们根据每个代理采用的认知架构模型,对比了代理对环境的适应情况。在这方面,我们发现有证据表明,时间异质性可能有助于更快地找到参数优化方案,以及其他好处。从定性的角度来看,我们研究了该模型在探索虚拟代理认知过程方面的潜力,得出的结论是需要对感知进行不同的表述,我们将对此进行进一步讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal heterogeneity in cognitive architectures

In 2020, Mc Fadden published an article in which he discusses how algorithms can be encoded in time and space. By analyzing the topology of the cytoarchitecture of the brain, cognitive architectures can understand the underlying mechanisms that have led to the development of human intelligence in space. In this study, our focus lies in investigating temporal heterogeneity as a mechanism that the brain could have developed not solely as a biological constraint, but also as an evolutionary advantage. To accomplish this, we employed virtual agents within a virtual environment and constructed a prototype cognitive architecture. Subsequently, we compared the benefits and drawbacks of having this cognitive architecture operate under a model of temporal heterogeneity versus one characterized by temporal homogeneity. At the conclusion of the article, we present the results obtained from two perspectives. From a quantitative standpoint, we contrast the agents’ adaptation to the environment based on the cognitive architecture model employed by each agent. On this front, we found evidence that temporal heterogeneity might be useful in finding parameter optimizations faster, amongst other benefits. From a qualitative perspective, we examine the potential of this model to explore the cognitive processes of the virtual agents, concluding that a different representation of percepts is needed, which we further discuss.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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