First Advisor

Jack Semura

Date of Publication

1-29-1996

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Physics

Department

Physics

Language

English

Subjects

Genetic algorithms, Maximum entropy method

DOI

10.15760/etd.7120

Physical Description

1 online resource (50 p.)

Abstract

The Brandeis dice problem, originally introduced in 1962 by Jaynes as an illustration of the principle of maximum entropy, was solved using the genetic algorithm, and the resulting solution was compared with that obtained analytically. The effect of varying the genetic algorithm parameters was observed, and the optimum values for population size, mutation rate, and mutation interval were determined for this problem. The optimum genetic algorithm program was then compared to a completely random method of search and optimization. Finally, the genetic algorithm approach was extended to several variations of the original problem for which an analytical approach would be impractical.

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Comments

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Persistent Identifier

https://archives.pdx.edu/ds/psu/30460

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