Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations Export

@incollection{citeulike:2696554, abstract = {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.}, author = {Cliff, Dave and Miller, Geoffrey}, citeulike-article-id = {2696554}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/3-540-59496-5_300}, doi = {10.1007/3-540-59496-5_300}, journal = {Advances in Artificial Life}, keywords = {coevolution, ga, gp, learning, self\_organizing}, pages = {200--218}, posted-at = {2009-05-02 00:52:04}, priority = {2}, title = {Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations}, url = {http://dx.doi.org/10.1007/3-540-59496-5_300}, year = {1995} }

TY - CHAP ID - citeulike:2696554 L3 - citeulike-article-id:2696554 N2 - 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. JF - Advances in Artificial Life EP - 218 TI - Tracking the red queen: Measurements of adaptive progress in co-evolutionary simulations SP - 200 KW - coevolution KW - ga KW - gp KW - learning KW - self_organizing AU - Cliff, Dave AU - Miller, Geoffrey PY - 1995/// UR - http://dx.doi.org/10.1007/3-540-59496-5_300 ER -