Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology

Mario Hevia Fajardo; Per Kristian Lehre; Jamal Toutouh; Erik Hemberg; Una-May O'Reilly

doi:10.1007/978-981-99-8413-8_2

Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology

Mario Hevia Fajardo^*, Per Kristian Lehre, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly

^*Corresponding author for this work

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Competitive coevolutionary algorithms are used to model adversarial dynamics. The diversity of the adversarial populations can be changed with a spatial topology. To achieve more clarity in how a spatial topology impacts performance and complexity we introduce a spatial topology to a pairwise dominance coevolutionary algorithm named PDCoEA. The new algorithm is called STPDCoEA. We use a methodology for consistent algorithm comparison to empirically study the impact of topology, problem, and mutation rates on the dynamics and payoffs in STPDCoEA. We compare records of multi-run dynamics on three problems and observe that the spatial topology impacts the performance and diversity.

Original language	English
Title of host publication	Genetic Programming Theory and Practice XX
Editors	Stephan Winkler, Leonardo Trujillo, Charles Ofria, Ting Hu
Publisher	Springer Singapore
Pages	19-44
Number of pages	26
Edition	1
ISBN (Electronic)	9789819984138
ISBN (Print)	9789819984121, 9789819984152
DOIs	https://doi.org/10.1007/978-981-99-8413-8_2
Publication status	Published - 17 Feb 2024

Publication series

Name	Genetic and Evolutionary Computation
ISSN (Print)	1932-0167
ISSN (Electronic)	1932-0175

Access to Document

10.1007/978-981-99-8413-8_2

Turing AI Fellowship: Rigorous time-complexity analysis of co-evolutionary algorithms
Lehre, P. K. (Principal Investigator)
Engineering & Physical Science Research Council
1/01/21 → 31/12/25
Project: Research Councils

Cite this

Hevia Fajardo, M., Lehre, P. K., Toutouh, J., Hemberg, E., & O'Reilly, U.-M. (2024). Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. In S. Winkler, L. Trujillo, C. Ofria, & T. Hu (Eds.), Genetic Programming Theory and Practice XX (1 ed., pp. 19-44). (Genetic and Evolutionary Computation). Springer Singapore. https://doi.org/10.1007/978-981-99-8413-8_2

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abstract = "Competitive coevolutionary algorithms are used to model adversarial dynamics. The diversity of the adversarial populations can be changed with a spatial topology. To achieve more clarity in how a spatial topology impacts performance and complexity we introduce a spatial topology to a pairwise dominance coevolutionary algorithm named PDCoEA. The new algorithm is called STPDCoEA. We use a methodology for consistent algorithm comparison to empirically study the impact of topology, problem, and mutation rates on the dynamics and payoffs in STPDCoEA. We compare records of multi-run dynamics on three problems and observe that the spatial topology impacts the performance and diversity.",

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Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. / Hevia Fajardo, Mario ; Lehre, Per Kristian; Toutouh, Jamal et al.
Genetic Programming Theory and Practice XX. ed. / Stephan Winkler; Leonardo Trujillo; Charles Ofria; Ting Hu. 1. ed. Springer Singapore, 2024. p. 19-44 (Genetic and Evolutionary Computation).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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AB - Competitive coevolutionary algorithms are used to model adversarial dynamics. The diversity of the adversarial populations can be changed with a spatial topology. To achieve more clarity in how a spatial topology impacts performance and complexity we introduce a spatial topology to a pairwise dominance coevolutionary algorithm named PDCoEA. The new algorithm is called STPDCoEA. We use a methodology for consistent algorithm comparison to empirically study the impact of topology, problem, and mutation rates on the dynamics and payoffs in STPDCoEA. We compare records of multi-run dynamics on three problems and observe that the spatial topology impacts the performance and diversity.

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Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology

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Projects

Turing AI Fellowship: Rigorous time-complexity analysis of co-evolutionary algorithms

Cite this