Toggle Main Menu Toggle Search

Open Access padlockePrints

LEAF: A Toolkit for Developing Coordinated Learning Based MAS

Lookup NU author(s): Steve Lynden


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


This paper describes LEAF, the "Learning Agent based FIPA-Compliant Community Toolkit", a toolkit for developing multiagent systems coordinated using utility function assignment, based on collective intelligence by Wolpert et al. (1999). LEAF agents use machine learning techniques such as reinforcement learning to maximise local utility functions, where local utility functions are assigned to agents such that the maximisation of local utility by agents within a community maximises a global utility. LEAF provides support via a Java API for developing FIPA-compliant agent systems conforming to this framework, utilising the FIPA-OS agent toolkit, a Java based FIPA compliant agent construction toolkit.

Publication metadata

Author(s): Lynden SJ, Rana OF

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: International Workshop on Java for Parallel and Distributed Computing (JAVAPDC) held as part of the 17th International Parallel and Distributed Processing Symposium (IPDPS)

Year of Conference: 2003

Pages: 135-143

ISSN: 1530-2075

Publisher: IEEE Computer Society Press


DOI: 10.1109/IPDPS.2003.1213260

Library holdings: Search Newcastle University Library for this item

ISBN: 0769519261