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- W2905137532 abstract "A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Researchers classify hyper-heuristics according to the source of feedback during learning: Online learning hyper-heuristics learn while solving a given instance of a problem; Offline learning hyper-heuristics learn from a set of training instances, a method that can generalise to unseen instances.Genetic programming (GP) can be considered a specialization of the more widely known genetic algorithms (GAs) where each individual is a computer program. GP automatically generates computer programs to solve specified tasks. It is a method of searching a space of computer programs. GP can be used as a kind of hyper-heuristic to be a learning algorithm when it uses some feedback from the search process. Our research mainly uses genetic programming as offline hyper-heuristic approach to automatically design various heuristics for evolutionary programming." @default.
- W2905137532 created "2018-12-22" @default.
- W2905137532 creator A5087500832 @default.
- W2905137532 date "2018-11-01" @default.
- W2905137532 modified "2023-09-24" @default.
- W2905137532 title "Hyper-heuristic approaches to automatically designing heuristics as mutation operators for evolutionary programming on function classes" @default.
- W2905137532 hasPublicationYear "2018" @default.
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