Yufik Yan M
Virtual Structures Research, Inc., Potomac, MD 20854, USA.
Entropy (Basel). 2019 Mar 21;21(3):308. doi: 10.3390/e21030308.
This article proposes a theory of neuronal processes underlying cognition, focusing on the mechanisms of understanding in the human brain. Understanding is a product of mental modeling. The paper argues that mental modeling is a form of information production inside the neuronal system extending the reach of human cognition "beyond the information given" (Bruner, J.S., , 1973). Mental modeling enables forms of learning and prediction (learning with understanding and prediction via explanation) that are unique to humans, allowing robust performance under unfamiliar conditions having no precedents in the past history. The proposed theory centers on the notions of self-organization and emergent properties of collective behavior in the neuronal substrate. The theory motivates new approaches in the design of intelligent artifacts (machine understanding) that are complementary to those underlying the technology of machine learning.
本文提出了一种认知背后神经元过程的理论,重点关注人类大脑中的理解机制。理解是心理建模的产物。本文认为,心理建模是神经元系统内部信息产生的一种形式,它将人类认知的范围扩展到“给定信息之外”(布鲁纳,J.S.,1973)。心理建模实现了人类特有的学习和预测形式(通过理解学习和通过解释进行预测),使得在过去历史中没有先例的不熟悉条件下也能有稳健的表现。所提出的理论以神经元基质中自组织和集体行为涌现特性的概念为核心。该理论推动了智能人工制品(机器理解)设计中的新方法,这些方法与机器学习技术所依据的方法相辅相成。