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Efficient graph-based genetic programming representation with multiple outputs

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Abstract

In this work, we explore and study the implication of having more than one output on a genetic programming (GP) graph-representation. This approach, called multiple interactive outputs in a single tree (MIOST), is based on two ideas. First, we defined an approach, called interactivity within an individual (IWI), which is based on a graph-GP representation. Second, we add to the individuals created with the IWI approach multiple outputs in their structures and as a result of this, we have MIOST. As a first step, we analyze the effects of IWI by using only mutations and analyze its implications (i.e., presence of neutrality). Then, we continue testing the effectiveness of IWI by allowing mutations and the standard GP crossover in the evolutionary process. Finally, we tested the effectiveness of MIOST by using mutations and crossover and conducted extensive empirical results on different evolvable problems of different complexity taken from the literature. The results reported in this paper indicate that the proposed approach has a better overall performance in terms of consistency reaching feasible solutions.

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Authors and Affiliations

  1. Department of Computer Science, University of Essex, Colchester, CO4 3SQ, UK

    Edgar Galvan-Lopez

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  1. Edgar Galvan-Lopez
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Correspondence to Edgar Galvan-Lopez.

Additional information

This paper was supported by the Mexican Consejo Nacional de Ciencia y Tecnologia (CONACyT) for the postgraduate studies at University of Essex.

Edgar Galvan-Lopez received his B. Sc. in computer science from University of Veracruz, Mexico, in 1999. He received his M. Sc. in artificial intelligence from University of Veracruz, Mexico, in 2001. He is currently a Ph. D. candidate in the Deparment of Computing and Electronic Systems at the University of Essex, UK.

His research interests include evolutionary computation systems, mainly in the paradigms of genetic algorithms and genetic programming.

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Galvan-Lopez, E. Efficient graph-based genetic programming representation with multiple outputs. Int. J. Autom. Comput. 5, 81–89 (2008). https://doi.org/10.1007/s11633-008-0081-4

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  • DOI: https://doi.org/10.1007/s11633-008-0081-4

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