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Evolving Neural Networks for Artificial Intelligence

机译:不断发展的人工智能神经网络

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This article takes a brief look at the history of Artificial Intelligence (AI), from good old-fashioned AI (GOFAI) to situated and embodied AI (SEAI) and its relationship to cognitive incrementalism, wherein sensorimotor mechanisms form the basis for high-level cognition. Artificial neural networks (ANNs) designed and tuned by evolutionary algorithms (EAs) are discussed in terms of their potential contributions to SEAI. Though state-of-the-art evolutionary ANN (EANN) research has not fulfilled this promise, our script-based EANN system (SEVANN) is briefly introduced as a software tool for quickly testing the SEAI utility of neuro-computational models of various spatial and temporal granularities.
机译:本文简要介绍了人工智能(AI)的历史,从良好的老式AI(GOFAI)到定位和体现的AI(SEAI)及其与认知增量主义的关系,其中感觉运动机制是高水平人工智能的基础认识。讨论了由进化算法(EA)设计和调整的人工神经网络(ANN)对SEAI的潜在贡献。尽管最新的进化ANN(EANN)研究尚未实现这一诺言,但我们还是简要介绍了基于脚本的EANN系统(SEVANN)作为一种软件工具,用于快速测试各种空间的神经计算模型的SEAI效用和时间粒度。

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