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# 2 Empirical Analysis of Diversity Measures

The Artificial Ant, Even-5-Parity, and symbolic regression problems (using the Quartic polynomial and Rastrigin function) were introduced in Chapter 2. The problems are used here to explore diversity measures and the relationship between diversity and fitness. Table 4.1 contains the problem and experiment parameters for the following empirical investigation. These parameters were selected as they are commonly used in the literature and in many similar empirical studies. Note that the function set used here is typical for the Rastrigin function, whereas the Quartic problem typically only uses addition, subtraction, multiplication and division. The same function set are used for both to be consistent and do not use any ephemeral random constants. The Rastrigin problem is likely to be more difficult to solve without using ephemeral random constants. All experiments in this thesis were carried out using a modified version of the ECJ framework [Luke, 2004] and the Mersenne Twister random number generator [Matsumoto and Nishimura, 1998].

 Evolutionary algorithm Generational Population size 500 Stopping criterion Maximum generation = 51 Function sets Ant if_food_ahead, progn2, progn3 Parity and, or, nand, nor Quartic, Rastrigin + , -, *, p/, sin, cos, exp, log Terminal sets Ant left, right, move Parity D1, D2, D3, D4, D5 Quartic, Rastrigin x Tree generation Ramped half-n-half Initial depth 4 Maximum depth 10 Subtree crossover probability 1.0 Subtree crossover internal node selection prob. 0.9 Mutation probability 0.0 Selection method, size Tournament selection, size 4

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Next: 1 Diversity Measures Used Up: 4 Analysis of Diversity Previous: 1 Promoting Diversity   Contents
S Gustafson 2004-05-20