Title: Enhancing Malaca agents with learning

Authors: M. Amor, L. Fuentes, J.A. Valenzuela

Addresses: Dpto. Lenguajes y Ciencias de la Computacion, ETSI Informatica, Universidad de Malaga, Campus de Teatinos, E29071 Malaga, Spain. ' Dpto. Lenguajes y Ciencias de la Computacion, ETSI Informatica, Universidad de Malaga, Campus de Teatinos, E29071 Malaga, Spain. ' Dpto. Lenguajes y Ciencias de la Computacion, ETSI Informatica, Universidad de Malaga, Campus de Teatinos, E29071 Malaga, Spain

Abstract: Current Object-Oriented (OO) frameworks provided with Multi-Agent Systems (MASs) development toolkits incorporate core abstractions to implement the agent. However, these OO designs do not provide proper abstractions to modularise other extra-functional concerns (e.g., the learning property), which are normally intermingled with the agent functionality and spread over different classes or components The reusability of agent architectural components is drastically reduced, so agents are difficult to maintain, extend or adapt. Aspect-oriented technologies overcome these problems by modelling such concerns as aspects. This work proposes to separate and modularise the learning of software agents following the aspectoriented solution of the Malaca model.

Keywords: software engineering; software agents; AOSD; aspect-oriented software development; agent learning; modelling; multi-agent systems; MAS; agent-based systems.

DOI: 10.1504/IJIIDS.2010.032439

International Journal of Intelligent Information and Database Systems, 2010 Vol.4 No.2, pp.137 - 155

Received: 30 Sep 2008
Accepted: 22 Nov 2008

Published online: 02 Apr 2010 *

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