G. Harik, E. Cant-Paz, D. E. Goldberg, and B. L. Miller, "The gambler 's ruin problem, genetic algorithms, and the sizing of populations," Evolut. Computat., vol. 7, no. 3, pp. 231--253, 1999. Home/Search Document Details and Download
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....ecological models (biological arms races, host parasite co evolution, symbiosis, ressource flow) Designing a GA can be a very difficult. Beside the mentioned tasks of defining a fitness function and the chromosome coding, Harik et al. considers the size of the population as a further parameter [42]. They provide a model for predicting the convergence quality of GA depending on the size. GAs have been used in various research projects to draw natural looking graphics [102] evolve virtual creatures [103] simulate a ant colony and their evolution [25] or generate robot configurations [68] ....
Harik, Cantu-Paz, Goldberg, and Miller. "The gambler's ruin problem, genetic algorithms, and the sizing of populations." In IEEECEP: Proceedings of The IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, 1997.
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G. Harik, E. Cant-Paz, D. E. Goldberg, and B. L. Miller, "The gambler 's ruin problem, genetic algorithms, and the sizing of populations," Evolut. Computat., vol. 7, no. 3, pp. 231--253, 1999.
Learning Gene Linkage to Efficiently Solve Problems of Bounded.. - Harik (1997) (24 citations) Self-citation (Harik Goldberg) (Correct)
....among two competing schemata on the basis of only one sample. GA approaches its expected behavior and the requisite building blocks grow. How large the population size needs to be to ensure building block growth is a question of accurate decision making at the level of the partition [36] 9] 25] [35]. Each of the schemata the GA needs to propagate is in competition with others over the same partition. Although the preferred schema has the highest average fitness, noise from the remainder of the chromosome can cause another schema to manifest a higher fitness in any pair of instances of the ....
....uniformly scaled problems. 5.3.3 Simple GAs and Uniformly Scaled Problems The simplest uniformly scaled problem, that of counting ones in the chromosome (onemax, has been studied extensively. The GA has been found to require O( p l) generations [55] and a population size of O( p l ln l) [35] 2 in order to solve this problem with any given probability of success. As one max is the simplest uniformly scaled problem, the combined time complexity of O(l ln l) is seen to be a lower bound for the time complexity required to solve these types of problems. Even when uniformly scaled ....
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G. Harik, E. Cantu-Paz, D. E. Goldberg, and B. L. Miller, "The gambler's ruin problem, genetic algorithms, and the sizing of populations," Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, pp. 7--12, 1997.
Low-Thrust Trajectory Optimization Using Stochastic Optimization .. - Hartmann (1999) (Correct)
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Harik, G., Cant-Paz, E., Goldberg, D., and Miller, B., "The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations," Proceedings of the 1997 IEEE Conference on Evolutionary Computation, edited by T. Back, IEEE Press, New York, 1997, pp. 7-12.
Time Series Datamining: Identifying Temporal Patterns For.. - Povinelli (1999) (1 citation) (Correct)
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G. R. Harik, E. Cant-Paz, D. E. Goldberg, and B. L. Miller, "The gambler 's ruin problem, genetic algorithms, and the sizing of populations," proceedings of IEEE Conference on Evolutionary Computation, 1997, pp. 7-12.
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