Title: Combining humans and machines into a cooperative multi-agent learning system

Authors: Herna L. Viktor

Addresses: Department of Informatics, University of Pretoria, Pretoria, 0002, South Africa

Abstract: This paper introduces a new methodology that combines human learners and inductive machine learners, which learn from data, into a cooperative multi-agent learning system. Educational cooperative learning techniques are used to model computational cooperative learning systems, which are used to facilitate the discovery of new knowledge to be used for classification purposes. The combination of humans and machines into a cooperative multi-agent learning system entails the marriage of the data-driven inductive machine learning approach with the knowledge-driven traditional knowledge-acquisition method. Results show that this approach succeeds in addressing the knowledge-acquisition bottleneck.

Keywords: learning agents; multi-agent learning; cooperative learning; human-computer interaction; knowledge acquisition.

DOI: 10.1504/IJCEELL.2002.000436

International Journal of Continuing Engineering Education and Life-Long Learning, 2002 Vol.12 No.1/2/3/4, pp.288-298

Published online: 16 Jul 2003 *

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