|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Title:||Comparing hyper-heuristics with blackboard systems|
|Citation:||Graham K & Smith L (2017) Comparing hyper-heuristics with blackboard systems In: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017, New York: Association for Computing Machinery, Inc. GECCO 2017: The Genetic and Evolutionary Computation Conference, 15.7.2017 - 19.7.2017, Berlin, Germany, pp. 1141-1145.|
|Conference Name:||GECCO 2017: The Genetic and Evolutionary Computation Conference|
|Conference Location:||Berlin, Germany|
|Abstract:||This paper aims to draw a comparison between the traditional view of hyper-heuristics and a lesser known type of multi-agent system known as a blackboard system. Both approaches share many similarities in both implementation and philosophy but also have several important differences in terms of characteristics and approach, such as a difference in control scheme. To investigate the consequences of the perceived differences, both approaches are decomposed into their constituent parts and compared with a focus on the perceived strengths and weaknesses of adopting one methodology over the other.|
|Status:||Book Chapter: publisher version|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|p1141-graham.pdf||627.38 kB||Adobe PDF||Under Permanent Embargo Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.