Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Recombination, selection, and the genetic construction of computer programs
Recombination, selection, and the genetic construction of computer programs
The royal tree problem, a benchmark for single and multiple population genetic programming
Advances in genetic programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming
Genetic Programming and Evolvable Machines
A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming
Evolutionary Computation
Evolving High-Speed, Easy-to-Understand Network Intrusion Detection Rules with Genetic Programming
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
A linear genetic programming approach to intrusion detection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Open issues in genetic programming
Genetic Programming and Evolvable Machines
The tree-string problem: an artificial domain for structure and content search
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Genetic programming needs better benchmarks
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Autoconstructive evolution for structural problems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Better GP benchmarks: community survey results and proposals
Genetic Programming and Evolvable Machines
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The NK landscapes are a well known benchmark for genetic algorithms (GAs) in which it is possible to tune the ruggedness of the fitness landscape by simply modifying the value of a parameter K. They have successfully been used in many theoretical studies, allowing researchers to discover interesting properties of the GAs dynamics in presence of rugged landscapes. A similar benchmark does not exist for genetic programming (GP) yet. Nevertheless, during the EuroGP conference debates of the last few years, the necessity of defining new benchmark problems for GP has repeatedly been expressed by a large part of the attendees. This paper is intended to fill this gap, by introducing an extension of the NK landscapes to tree based GP, that we call K landscapes. In this benchmark, epistasis are expressed as growing mutual interactions between the substructures of a tree as the parameter K increases. The fact that the problem becomes more and more difficult as the value of K increases is experimentally demonstrated. Interestingly, we also show that GP "bloats" more and more as K increases.