Natural Computing

, Volume 5, Issue 3, pp 229–255 | Cite as

The dynamics of the best individuals in co-evolution

  • Elena Popovici
  • Kenneth De Jong


There continues to be a growing interest in the use of co-evolutionary algorithms to solve difficult computational problems. However, their performance has varied widely from good to disappointing. The main reason for this is that co-evolutionary systems can display quite complex dynamics. Therefore, in order to efficiently use co-evolutionary algorithms for problem solving, one must have a good understanding of their dynamical behavior. To build such understanding, we have constructed a methodology for analyzing co-evolutionary dynamics based on trajectories of best-of-generation individuals. We applied this methodology to gain insights into how to tune certain algorithm parameters in order to improve performance.


best-response co-evolution dynamics cooperative co-evolution optimization performance 


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We would like to thank: Gabriel Balan, for pointing out the “best-response” terminology as appropriate for our work; An anonymous reviewer of our paper (Popovici and De Jong, 2005a), for suggesting parameterizing the angle between the best-response curves; Jayshree Sarma, for proof reading the manuscript and providing useful comments that we incorporated for improving the paper.


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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.George Mason UniversityFairfaxUSA

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