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What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming.

, , , , , , and . Genet. Program. Evolvable Mach., 2 (2): 165-191 (2001)

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What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming., , , , , and . GECCO, page 982-989. Morgan Kaufmann, (1999)Challenges with Verification, Repeatability, and Meaningful Comparison in Genetic Programming: Gibson's Magic., , , , and . GECCO, page 1851-1858. Morgan Kaufmann, (1999)Reconnoiter by Candle: Identifying Assumptions in Genetic Programming. Foundations of Genetic Programming, page 53--54. Orlando, Florida, USA, (13 July 1999)Analysis of Single-Node (Building) Blocks in Genetic Programming, , , and . Advances in Genetic Programming 3, chapter 10, MIT Press, Cambridge, MA, USA, (June 1999)Characterizing the dynamics of symmetry breaking in genetic programming.. GECCO, page 799-806. ACM, (2006)Towards identifying populations that increase the likelihood of success in genetic programming.. GECCO, page 1627-1634. ACM, (2005)Optimal Mutation and Crossover Rates for a Genetic Algorithm Operating in a Dynamic Environment., and . Evolutionary Programming, volume 1447 of Lecture Notes in Computer Science, page 693-702. Springer, (1998)(1+1) genetic algorithm fitness dynamics in a changing environment., and . CEC, page 1851-1858. IEEE, (1999)Demonstrating constraints to diversity with a tunably difficult problem for genetic programming., , , , and . IEEE Congress on Evolutionary Computation, page 1217-1224. IEEE, (2004)Limits to expression in genetic programming: lattice-aggregate modeling.. IEEE Congress on Evolutionary Computation, page 273-278. IEEE, (2002)