The Max problem revisited: the importance of mutation in genetic programming

DOI10.1016/J.TCS.2013.06.014zbMath1360.68782OpenAlexW2063653388MaRDI QIDQ2250999

Frank Neumann, Timo Kötzing, Una-May O'Reilly, Andrew M. Sutton

Publication date: 10 July 2014

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2013.06.014

zbMATH Keywords

genetic programmingtheorymutationruntime analysis

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (2)

(1+1) genetic programming with functionally complete instruction sets can evolve Boolean conjunctions and disjunctions with arbitrarily small error ⋮ Mathematical analysis of the cumulative effect of novel ternary crossover operator and mutation on probability of survival of a schema

Cites Work

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• Bioinspired computation in combinatorial optimization. Algorithms and their computational complexity
• Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics
• Non-uniform mutation rates for problems with unknown solution lengths
• Limit Theorems in an Occupancy Problem
• Evolvability

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