EA models and population fixed-points versus mutation rates for functions of unitation

Using a dynamic systems model for the Simple Genetic Algorithm due to Vose[1], we analyze the fixed point behavior of the model without crossover applied to functions of unitation. Unitation functions are simplified fitness functions that reduce the search space into a smaller number of equivalence classes. This reduction allows easier computation of fixed points. We also create a dynamic systems model from a simple nondecreasing EA like the (1+1) EA and variants, then analyze this models on unitation classes. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]:Problem Solving, Control Methods, and Search – Genetic Algorithms. General Terms Algorithms, Artificial Intelligence Keywords theory of evolutionary algorithms, infinite population models, unitation functions, fixed points, genetic algorithms.

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: J. Neal Richter, John Paxton, Alden H. Wright
• Keywords: Dynamic Systems Model, Fixed Points, GECCO 2005, Genetic Algorithms