期刊
COGNITIVE COMPUTATION
卷 6, 期 1, 页码 66-73出版社
SPRINGER
DOI: 10.1007/s12559-013-9201-8
关键词
Hyper-heuristics; Metaheuristics; Optimization; Machine-learning; Blackboard architecture
资金
- EPSRC [EP/H000968/1, EP/F033214/1, EP/D061571/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/H000968/1, EP/F033214/1, EP/D061571/1] Funding Source: researchfish
We extend a previous mathematical formulation of hyper-heuristics to reflect the emerging generalization of the concept. We show that this leads naturally to a recursive definition of hyper-heuristics and to a division of responsibility that is suggestive of a blackboard architecture, in which individual heuristics annotate a shared workspace with information that may also be exploited by other heuristics. Such a framework invites consideration of the kind of relaxations of the domain barrier that can be achieved without loss of generality. We give a concrete example of this architecture with an application to the 3-SAT domain that significantly improves on a related token-ring hyper-heuristic.
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