TY - GEN
T1 - Predicting genetic drift in 2x2 games
AU - Liekens, A.M.L.
AU - Eikelder, ten, H.M.M.
AU - Hilbers, P.A.J.
PY - 2004
Y1 - 2004
N2 - For the analysis of the dynamics of game playing populations, it is common practice to assume infinitely large populations. Infinite models yield predictions of fixed points and their stability properties. However, these models cannot demonstrate the influence of genetic drift, caused by stochastic sampling in small populations. Instead, we propose Markov models of finite populations for the analysis of genetic drift in games. With these exact models, we can study the stability of evolutionary stable strategies, and measure the influence of genetic drift in the long run. We show that genetic drift can introduce significant differences in the expectations of long term behavior.
AB - For the analysis of the dynamics of game playing populations, it is common practice to assume infinitely large populations. Infinite models yield predictions of fixed points and their stability properties. However, these models cannot demonstrate the influence of genetic drift, caused by stochastic sampling in small populations. Instead, we propose Markov models of finite populations for the analysis of genetic drift in games. With these exact models, we can study the stability of evolutionary stable strategies, and measure the influence of genetic drift in the long run. We show that genetic drift can introduce significant differences in the expectations of long term behavior.
UR - http://www.scopus.com/inward/record.url?scp=35048832384&partnerID=8YFLogxK
M3 - Conference contribution
SN - 3-540-22344-4
VL - 3102
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 549
EP - 560
BT - Genetic and Evolutionary Computation (Proceedings GECCO 2004, Seattle WA, USA, June 26-30, 2004)
A2 - Deb, K.
PB - Springer
CY - Berlin
ER -