A Stochastic Hyperheuristic for Unsupervised Matching of Partial Information. (31st October 2012)
- Record Type:
- Journal Article
- Title:
- A Stochastic Hyperheuristic for Unsupervised Matching of Partial Information. (31st October 2012)
- Main Title:
- A Stochastic Hyperheuristic for Unsupervised Matching of Partial Information
- Authors:
- Greer, Kieran
- Other Names:
- Mandl Thomas Academic Editor.
- Abstract:
- 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.
- Is Part Of:
- Advances in artificial intelligence. Volume 2012(2012)
- Journal:
- Advances in artificial intelligence
- Issue:
- Volume 2012(2012)
- Issue Display:
- Volume 2012, Issue 2012 (2012)
- Year:
- 2012
- Volume:
- 2012
- Issue:
- 2012
- Issue Sort Value:
- 2012-2012-2012-0000
- Page Start:
- Page End:
- Publication Date:
- 2012-10-31
- Subjects:
- Artificial intelligence -- Periodicals
Artificial intelligence
Periodicals
Electronic journals
006.3 - Journal URLs:
- https://www.hindawi.com/journals/aai/ ↗
- DOI:
- 10.1155/2012/790485 ↗
- Languages:
- English
- ISSNs:
- 1687-7470
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 16115.xml