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Intentional systems: Review of neurodynamics, modeling, and robotics implementation

机译:意图系统:神经动力学,建模和机器人技术实现的回顾

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摘要

We present an intentional neurodynamic theory for higher cognition and intelligence. This theory provides a unifying framework for integrating symbolic and subsymbolic methods as complementary aspects of human intelligence. Top-down symbolic approaches benefit from the vast experience with logical reasoning and with high-level knowledge processing in humans. Connectionist methods use bottom-up approach to generate intelligent behavior by mimicking subsymbolic aspects of the operation of brains and nervous systems. Neurophysiological correlates of intentionality and cognition include sequences of oscillatory patterns of mesoscopic neural activity. Oscillatory patterns are viewed as intermittent representations of generalized symbol systems, with which brains compute. These dynamical symbols are not rigid but flexible. They disappear soon after they emerged through spatio-temporal phase transitions. Intentional neurodynamics provides a solution to the notoriously difficult symbol grounding problem. Some examples of implementations of the corresponding dynamic principles are described in this review.
机译:我们提出了一种旨在提高认知和智力的神经动力学理论。该理论提供了一个统一的框架,用于将符号和亚符号方法整合为人类智能的补充方面。自上而下的符号方法得益于人类逻辑推理和高级知识处理方面的丰富经验。连接主义方法使用自下而上的方法,通过模仿大脑和神经系统操作的符号下方面来生成智能行为。意向性和认知的神经生理相关性包括介观神经活动的振荡模式序列。振荡模式被看作是大脑进行计算的广义符号系统的间歇性表示。这些动态符号不是刚性的而是柔性的。它们通过时空相变出现后不久就消失了。故意的神经动力学为众所周知的困难符号接地问题提供了解决方案。在这篇评论中描述了相应动态原理的一些实现示例。

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