Statistical Features in Learning
凝聚态物理
2007-05-23 v2 adap-org
适应与自组织系统
摘要
We study some features of learning models based on "delayed" and undifferentiated reinforcement and realized by simple algorithms which may be considered of a very elementary nature. We show that a modification of the Hebb-rule works well for this problem in a neural network realization and study numerically its convergence properties. An illustration for a more "concrete" situation is provided.
引用
@article{arxiv.cond-mat/9809135,
title = {Statistical Features in Learning},
author = {Ion-Olimpiu Stamatescu},
journal= {arXiv preprint arXiv:cond-mat/9809135},
year = {2007}
}
备注
13 pages, 7 figures; LEARNING'98 Madrid; 2 notations, 1 typo corrected