Self-emergence of structures in gene expression programming

Authors:
Xin Li
Affiliations:
Department of Computer Science, University of Illinois at Chicago, Chicago, IL
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Year:
2005

Citing 4
Cited 0

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Genetic programming II: automatic discovery of reusable programs

Genetic programming II: automatic discovery of reusable programs
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)

Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Evolving accurate and compact classification rules with gene expression programming

IEEE Transactions on Evolutionary Computation

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Abstract

This thesis work aims at improving the problem solving ability of the Gene Expression Programming (GEP) algorithm to fulfill complex data mining tasks by preserving and utilizing the self-emergence of structures during its evolutionary process. The main contributions include the investigation of the constant creation techniques for promoting good functional structures emergent in the evolution, analysis of the limitation with the current implementation scheme of GEP, and introduction of a novel utilization of the emergent structures to achieve a flexible search process for solutions at a higher level.