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Advances in Artificial Intelligence
Volume 2012 (2012), Article ID 790485, 8 pages
http://dx.doi.org/10.1155/2012/790485
Research Article

A Stochastic Hyperheuristic for Unsupervised Matching of Partial Information

Distributed Computing Systems, Belfast, UK

Received 28 May 2012; Accepted 21 September 2012

Academic Editor: Thomas Mandl

Copyright © 2012 Kieran Greer. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper (Revised version of a white paper “Unsupervised Problem-Solving by Optimising through Comparisons,” originally published on DCS and Scribd, October 2011.) describes the implementation and functionality of a centralised problem solving system that is included as part of the distributed “licas” system. This is an open source framework for building service-based networks, similar to what you would do on a Cloud or SOA platform. While the framework can include autonomous and distributed behaviour, the problem-solving part can perform more complex centralised optimisation operations and then feed the results back into the network. The problem-solving system is based on a novel type of evaluation mechanism that prefers comparisons between solution results, over maximisation. This paper describes the advantages of that and gives some examples of where it might perform better, including possibilities related to a more cognitive system.