Opposition-based learning: A new scheme for machine intelligence

被引：1824

作者：

Tizhoosh, Hamid R. ^{[1
]}

机构：

[1] Univ Waterloo, Pattern Anal & Machine Intelligence Lab, Waterloo, ON N2L 3G1, Canada

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION JOINTLY WITH INTERNATIONAL CONFERENCE ON INTELLIGENT AGENTS, WEB TECHNOLOGIES & INTERNET COMMERCE, VOL 1, PROCEEDINGS | 2006年

关键词：

D O I：

10.1109/cimca.2005.1631345

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions are the foundation of this new approach. Examples are provided Possibilities for extensions of existing, learning algorithms are discussed. Preliminary results are provided.

引用

页码：695 / 701

页数：7