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On neural networks for symbolic processing

机译:关于象征性的神经网络

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摘要

Existing approaches to integrating neural and symbolic processing are divided into the following four categories: developing specialized, structured, localist networks for symbolic processing; performing symbolic processing in distributed neural networks (in a holistic way); combining separate symbolic and neural network modules; and using neural networks as basic elements in symbolic architectures (the embedded approach). Research issues that need to be addressed in order to advance this field as well as to better understand the nature of intelligence and cognition are outlined.
机译:将神经和符号处理集成的现有方法分为以下四类:开发专业,结构化的局部网络,用于符号处理;在分布式神经网络中执行象征性处理(以整体方式);结合单独的符号和神经网络模块;并使用神经网络作为符号架构中的基本元素(嵌入方法)。需要解决的研究问题,以便提升这一领域以及更好地了解智力和认知的性质。

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