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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Node B is not necessarily isolated from A if node A is isolated from B.
References
Angeline, P.J., Pollack, J.B.: Competitive environments evolve better solutions for complex tasks. In: Proceedings of the Fifth International Conference (GA93), Genetic Algorithms, pp. 264–270 (1993)
Antonio, L.M., Coello, C.A.C.: Coevolutionary multi-objective evolutionary algorithms: a survey of the state-of-the-art. IEEE Trans. Evolut. Comput. 1–16 (2018)
Axelrod, R.: The Evolution of Cooperation, vol. 10. Basic, New York (1984)
Cardona, A.B., Togelius, J., Nelson, M.J.: Competitive coevolution in ms. pac-man. In: 2013 IEEE Congress on Evolutionary Computation, pp. 1403–1410 (2013)
Corus, D., Dang, D.C., Eremeev, A.V., Lehre, P.K.: Level-based analysis of genetic algorithms and other search processes. IEEE Trans. Evol. Comput. 22(5), 707–719 (2018)
Czarnecki, W.M., Gidel, G., Tracey, B., Tuyls, K., Omidshafiei, S., Balduzzi, D., Jaderberg, M.: Real world games look like spinning tops. Adv. Neural. Inf. Process. Syst. 33, 17443–17454 (2020)
van Dijk, M., Juels, A., Oprea, A., Rivest, R.L.: FlipIt: The game of “Stealthy Ttakeover. J. Cryptol. 26(4), 655–713 (2013)
Droste, S., Jansen, T., Wegener, I.: On the analysis of the (1+1) evolutionary algorithm. Theoret. Comput. Sci. 276(1–2), 51–81 (2002)
Ehrlich, P.R., Raven, P.H.: Butterflies and plants: a study in coevolution. Evolution 18(4), 586–608 (1964)
Eigen, M.: Selforganization of matter and the evolution of biological macromolecules. Naturwissenschaften 58(10), 465–523 (1971)
Ficici, S.G.: Solution concepts in coevolutionary algorithms. Ph.D. thesis, Brandeis University (2004)
Fogel, D.: Blondie24: playing at the edge of artificial intelligence (2001)
Goldberg, D.E.: Genetic algorithms in search, optimization and machine learning, 1st edn. Addison-Wesley Longman Publishing Co. Inc, Boston (1989)
Hemberg, E., Rosen, J., Warner, G., Wijesinghe, S., O’Reilly, U.M.: Detecting tax evasion: a co-evolutionary approach. Artif. Intell. Law 24, 149–182 (2016)
Hemberg, E., Toutouh, J., Al-Dujaili, A., Schmiedlechner, T., O’Reilly, U.M.: Spatial coevolution for generative adversarial network training. ACM Trans. Evol. Learn. Optim. 1(2) (2021)
Jones, S.T., Outkin, A.V., Gearhart, J.L., Hobbs, J.A., Siirola, J.D., Phillips, C.A., Verzi, S.J., Tauritz, D., Mulder, S.A., Naugle, A.B.: Evaluating moving target defense with pladd. Technical report, Sandia National Lab.(SNL-NM), Albuquerque, NM (United States) (2015)
Krawiec, K., Heywood, M.: Solving complex problems with coevolutionary algorithms. In: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, pp. 687–713. ACM (2016)
Lehre, P.K.: Negative drift in populations. In: Proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN 2010). LNCS, vol. 6238, pp. 244–253. Springer, Berlin (2010)
Lehre, P.K.: Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear function. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO ’22, pp. 1408–1416. ACM, New York (2022)
Lehre, P.K., Hevia Fajardo, M., Hemberg, E., Toutouh, J., O’Reilly, U.M.: Analysis of a pairwise dominance coevolutionary algorithm and defendit. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO ’23. ACM, New York (2023)
Lim, C.U., Baumgarten, R., Colton, S.: Evolving behaviour trees for the commercial game DEFCON. In: European Conference on the Applications of Evolutionary Computation, pp. 100–110. Springer (2010)
Luke, S., et al.: Genetic programming produced competitive soccer softbot teams for robocup97. Genet. Program. 1998, 214–222 (1998)
Mitchell, M.: Coevolutionary learning with spatially distributed populations. Comput. Intell.: Princip. Pract. 400 (2006)
Ochoa, G.: Error thresholds in genetic algorithms. Evol. Comput. 14(2), 157–182 (2006)
O’Reilly, U.M., Toutouh, J., Pertierra, M., Sanchez, D.P., Garcia, D., Luogo, A.E., Kelly, J., Hemberg, E.: Adversarial genetic programming for cyber security: a rising application domain where gp matters. Genet. Program Evolvable Mach. 21, 219–250 (2020)
Popovici, E., Bucci, A., Wiegand, R.P., De Jong, E.D.: Coevolutionary Principles, pp. 987–1033. Springer, Berlin (2012)
Rosin, C.D., Belew, R.K.: New methods for competitive coevolution. Evol. Comput. 5(1), 1–29 (1997)
Sims, K.: Evolving 3d morphology and behavior by competition. Artif. Life 1(4), 353–372 (1994)
Togelius, J., Burrow, P., Lucas, S.M.: Multi-population competitive co-evolution of car racing controllers. In: 2007 IEEE Congress on Evolutionary Computation, pp. 4043–4050 (2007)
Tomassini, M.: Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time. Springer (2005)
Toutouh, J., O’Reilly, U.M.: Signal propagation in a gradient-based and evolutionary learning system. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 377–385 (2021)
Acknowledgements
Lehre and Hevia were supported by a Turing AI Fellowship (EPSRC grant ref EP/V025562/1).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Hevia Fajardo, M., Lehre, P.K., Toutouh, J., Hemberg, E., O’Reilly, UM. (2024). Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. In: Winkler, S., Trujillo, L., Ofria, C., Hu, T. (eds) Genetic Programming Theory and Practice XX. Genetic and Evolutionary Computation. Springer, Singapore. https://doi.org/10.1007/978-981-99-8413-8_2
Download citation
DOI: https://doi.org/10.1007/978-981-99-8413-8_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-8412-1
Online ISBN: 978-981-99-8413-8
eBook Packages: Computer ScienceComputer Science (R0)