Extensions to behavioral genetic programming
Author(s)
Fine, Steven B
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Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Una-May O'Reilly.
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In this work I introduce genetic programming [5] as a general technique to produce programs with arbitrary behavior. I discuss genetic programming and its application the task of symbolic regression. I introduce behavioral genetic programming [6] as an extension to genetic programming and explore various extensions to it. The codebase that I build is made sufficiently flexible to easily accommodate future adaptions to the behavioral genetic programming methodology. I test the performance of the implementation of behavioral genetic programming along with several extensions.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (page 55).
Date issued
2017Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.