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Tag-based modules in genetic programming

Item Type:Conference or Workshop Item
Title:Tag-based modules in genetic programming
Creators Name:Spector, L. and Martin, B. and Harrington, K. and Helmuth, T.
Abstract:In this paper we present a new technique for evolving modular programs with genetic programming. The technique is based on the use of "tags" that evolving programs may use to label and later to refer to code fragments. Tags may refer inexactly, permitting the labeling and use of code fragments to co-evolve in an incremental way. The technique can be implemented as a minor modification to an existing, general purpose genetic programming system, and it does not require pre-specification of the module architecture of evolved programs. We demonstrate that tag-based modules readily evolve and that this allows problem solving effort to scale well with problem size. We also show that the tag-based module technique is effective even in complex, non-uniform problem environments for which previous techniques perform poorly. We demonstrate the technique in the context of the stack-based genetic programming system PushGP, but we also briefly discuss ways in which it may be used with other kinds of genetic programming systems.
Keywords:Push, PushGP, Genetic Programming, Stack-Based Genetic Programming, Modularity, Automatically Defined Functions, Tags, Lawnmower Problem, Obstacle-Avoiding Robot Problem
Source:Proceedings of the Conference on Genetic and Evolutionary Computation
Title of Book:Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11
Publisher:Association for Computing Machinery
Page Range:1419
Date:July 2011
Official Publication:https://doi.org/10.1145/2001576.2001767

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