Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations
- First Online:
- Cite this paper as:
- Cliff D., Miller G.F. (1995) Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations. In: Morán F., Moreno A., Merelo J.J., Chacón P. (eds) Advances in Artificial Life. ECAL 1995. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 929. Springer, Berlin, Heidelberg
Co-evolution can give rise to the “Red Queen effect”, where interacting populations alter each other's fitness landscapes. The Red Queen effect significantly complicates any measurement of co-evolutionary progress, introducing fitness ambiguities where improvements in performance of co-evolved individuals can appear as a decline or stasis in the usual measures of evolutionary progress. Unfortunately, no appropriate measures of fitness given the Red Queen effect have been developed in artificial life, theoretical biology, population dynamics, or evolutionary genetics. We propose a set of appropriate performance measures based on both genetic and behavioral data, and illustrate their use in a simulation of co-evolution between genetically specified continuous-time noisy recurrent neural networks which generate pursuit and evasion behaviors in autonomous agents.
Unable to display preview. Download preview PDF.