Evolving Neural Networks for Artificial Intelligence

被引:0
作者
Downing, Keith L. [1 ]
机构
[1] Norwegian Univ Sci & Technol, Trondheim, Norway
来源
BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 2011 | 2011年 / 233卷
关键词
evolutionary algorithms; artificial neural networks; cognitive incrementalism; EVOLUTION;
D O I
10.3233/978-1-60750-959-2-96
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 neurocomputational models of various spatial and temporal granularities.
引用
收藏
页码:96 / 102
页数:7
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