Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/16329
Title: Evolutionary computation based genetic machine learning
Researcher: Thaker, Chirag Suryakant
Guide(s): Singh, Dharm
Shah, J S
Keywords: Computer Science
Genetic machine learning
Upload Date: 25-Feb-2014
University: Suresh Gyan Vihar University
Completed Date: November, 2012
Abstract: Since centuries board games have been very prominent facet of human life. It has played very imperative and pivotal role as research area in the field of Artificial Intelligence since many decades. Machine learning based systems have shown the penchant of constantly evolving and improving and always preserves its truthfulness as a learning system. The notion of constructing computer programs modelled on move making is motivational drive for systems which reveal acumen, wisdom aptitude and self-adaptation. The game playing programs tries to imitate human game playing approach in its own limited operative possibilities. Such competences can be well explored in an important domains like board games of two-player, zero-sum, deterministic, perfect information and alternate move. The thesis takes Game of Checkers and Game of Reversi as its test bed games of research to address computer program based learning by addressing search complexity and decision complexity of them. Research uses min-max search with alpha-beta pruning to address the issue of search complexity. It takes novel approach in forming genetic string that is based on study of important board game features. These genetic strings act as evaluation functions which are evolved using various genetic parameters for a specified size of population for iterative generations in a given set of number of games to find near optimal solution. These evolved weights are used to make move making decision that addresses decision complexity. The collected set of fitness weight values for different disc positions and generations imply the evolutionary learning of board game computer programs.
Pagination: iv, 235p.
URI: http://hdl.handle.net/10603/16329
Appears in Departments:Department of Computer Science

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02_certificate.pdf181.43 kBAdobe PDFView/Open
03_acknowledgement.pdf215.51 kBAdobe PDFView/Open
04_abstract.pdf50 kBAdobe PDFView/Open
05_list of abberviation.pdfAttached File61.32 kBAdobe PDFView/Open
06_list of figure.pdf132.7 kBAdobe PDFView/Open
07_list of tables.pdf57.77 kBAdobe PDFView/Open
08_content.pdf134.51 kBAdobe PDFView/Open
09_chapter 1.pdf558.27 kBAdobe PDFView/Open
10_chapter 2.pdf563.97 kBAdobe PDFView/Open
11_chapter 3.pdf466.29 kBAdobe PDFView/Open
12_chapter 4.pdf1.99 MBAdobe PDFView/Open
13_chapter 5.pdf150.92 kBAdobe PDFView/Open
14_chapter 6.pdf72.76 kBAdobe PDFView/Open
15_chapter 7.pdf144.42 kBAdobe PDFView/Open
16_chapter 8.pdf87.6 kBAdobe PDFView/Open


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