Information storage capacity of genetic algorithm fitness maps.
| dc.contributor.advisor | Hamerly, Gregory James, 1977- | |
| dc.contributor.author | MontaƱez, George D. | |
| dc.contributor.department | Computer Science. | en_US |
| dc.contributor.schools | Baylor University. Dept. of Computer Science. | en_US |
| dc.date.accessioned | 2011-09-14T13:00:54Z | |
| dc.date.available | 2011-09-14T13:00:54Z | |
| dc.date.copyright | 2011-08 | |
| dc.date.issued | 2011-09-14 | |
| dc.description.abstract | To accurately measure the amount of information a genetic algorithm can generate, we must first measure the amount of information one can store, using a fitness map. The amount of information generated, minus the storage capacity, gives a tighter estimate on the levels of information generated by genetic algorithms. To measure the information storage capacity of fitness maps, we use the method suggested by Abu-Mostafa et al. (Abu-Mostafa and St Jacques, 1985) for measuring the information storage capacity of general forms of memory. Additionally, we measure the information in reference to the active information metric, as developed by Dembski et al. (Dembski and Marks, 2009). Our results show that a number of bits linear in the size of the search space can be stored in a fitness map, but only a logarithmic number of bits can be extracted by a genetic algorithm with stabilizing population and fixed population size. | en_US |
| dc.description.degree | M.S. | en_US |
| dc.identifier.uri | http://hdl.handle.net/2104/8233 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | en | |
| dc.rights | Baylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission. | en_US |
| dc.rights.accessrights | Worldwide access. | en_US |
| dc.rights.accessrights | Access changed 3/14/13. | |
| dc.subject | Genetic algorithms. | en_US |
| dc.subject | Fitness functions. | en_US |
| dc.subject | Information theory. | en_US |
| dc.subject | Storage complexity. | en_US |
| dc.title | Information storage capacity of genetic algorithm fitness maps. | en_US |
| dc.type | Thesis | en_US |
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