Title :
(1+1) genetic algorithm fitness dynamics in a changing environment
Author :
Stanhope, Stephen A. ; Daida, Jason M.
Author_Institution :
Artificial Intelligence Lab., Michigan Univ., Ann Arbor, MI, USA
Abstract :
We analyze the fitness dynamics of a (1+1) mutation-only genetic algorithm (GA) operating on a family of simple time-dependent fitness functions. Resulting models of behavior are used in the prediction of GA performance on this fitness function. The accuracy of performance predictions are compared to actual GA runs, and results are discussed in relation to analyses of the stationary version of the dynamic fitness landscape and to prior work performed in the field of evolutionary optimization of dynamic fitness functions
Keywords :
artificial life; genetic algorithms; performance evaluation; stochastic processes; GA performance; GA runs; behavior models; changing environment; dynamic fitness functions; dynamic fitness landscape; evolutionary optimization; genetic algorithm fitness dynamics; mutation-only genetic algorithm; performance predictions; prior work; simple time-dependent fitness functions; stationary version; Algorithm design and analysis; Artificial intelligence; Evolutionary computation; Genetic algorithms; Laboratories; Mathematical analysis; Mathematical model; Performance analysis; Physics; Predictive models;
Conference_Titel :
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5536-9
DOI :
10.1109/CEC.1999.785499
