From neurons to consciousness

D. Doval
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引用次数: 3

Abstract

This paper outlines a possible model for human intelligence, based on the fact that the act of understanding can be explained, at best, as an act of pure intuition, impossible to explain in itself. Based on the model, we discuss how learning could be accomplished by such a system, and how knowledge could be transferred between generations. The model uses clusters of neural networks to achieve its goal. The proposed model uses a genetic algorithm closely coupled to the memory neural cluster to achieve creativity and to generate original responses. Other issues, such as possible internal representation models, are also discussed. As the model is certainly intensive in terms of computing-power and memory, and several components remain to be clearly defined, a reduced model is proposed. We define a system that can only handle one type of input (voice) that will learn a limited number of procedures. This reduced system would provide a basis to test the actual feasibility of the model and its possibilities, as well as different subsystem implementations.
从神经元到意识
这篇论文概述了一个可能的人类智能模型,基于这样一个事实,即理解行为最多只能被解释为一种纯粹的直觉行为,而这种行为本身是无法解释的。基于该模型,我们讨论了这样一个系统如何完成学习,以及知识如何在代际之间传递。该模型使用神经网络集群来实现其目标。该模型将遗传算法与记忆神经簇紧密结合,实现创造性并生成原始响应。还讨论了其他问题,例如可能的内部表示模型。由于该模型在计算能力和内存方面确实是密集的,并且有几个组件仍有待明确定义,因此提出了一个简化模型。我们定义了一个只能处理一种输入(语音)的系统,它将学习有限数量的过程。这个简化的系统将提供一个基础来测试模型的实际可行性及其可能性,以及不同的子系统实现。
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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