Data processing: artificial intelligence – Machine learning – Genetic algorithm and genetic programming system
Reexamination Certificate
2007-09-18
2007-09-18
Knight, Anthony (Department: 2121)
Data processing: artificial intelligence
Machine learning
Genetic algorithm and genetic programming system
Reexamination Certificate
active
10793527
ABSTRACT:
Methods, systems, and articles of manufacture utilizing the biological principle of dominance to affect the operation of a genetic algorithm are provided. The genetic algorithm may be used to select a multi-parameter solution set to a user-defined problem, with each parameter modeled as a gene. Dominance may be introduced by associating a dominance attribute with one or more gene values (i.e., traits), for example, that are known to lead to good solution sets, allowing the corresponding gene values to be specified as dominant or recessive. By specifying the known good gene values as dominant, system performance may be optimized as the genetic algorithm may quickly arrive at a good solution set (e.g., due to the known good value appearing more often in future generations). On the other hand, by specifying the known good gene value as recessive, the search space may be increased as the genetic algorithm may evaluate a larger number of possible solution sets (e.g., due to the known good value appearing less often in future generations).
REFERENCES:
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David E. Goldberg, Robert E. Smith, “Nonstationary function optimization using genetic algorithm with dominance and diploidy”, Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application, 1987, pp. 59-68.
T Schnier, JS Gero, “Dominant and Recessive Genes in Evolutionary Systems Applied to Spatial Reasoning”, Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence , 1997, pp. 127-136.
J Lewis, E Hart, G Ritchie, “A comparison of dominance mechanisms and simple mutation on non-stationary problems”, Parallel Problem Solving from Nature—PPSN V: 5th International Conference Amsterdam, The Netherlands, Sep. 27-30, 1998 Proceedings, pp. 139-148.
Diedrich Michael J.
Diedrich Richard A.
Holmes Michael B.
Knight Anthony
Patterson & Sheridan
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