Date of Award

12-2004

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Engineering and Sciences

First Advisor

Gregory Harrison

Second Advisor

Richard James

Third Advisor

David E. Clapp

Fourth Advisor

William D. Shoaff

Abstract

The study of Artificial Intelligence attempts to simulate the processes of human intelligence in a set of computable algorithms. The purpose of Random Algorithms in this field is to provide a best-guess approach at identifying the unknown. In this thesis, research shows that random algorithms are able to break down many intelligent processes into a set of solvable problems. For example, solving puzzles and playing games involve the same estimating ability shown in standard problems such as the Coupon Collector problem or the Monty Hall problem. This thesis shows Random Algorithmic applications in two overlapping categories of intelligent behavior: Pattern Recognition (to solve puzzles) and Mind Simulation (to play games). The first category focuses on one of the prominent intelligent processes, recognizing patterns from randomness, which the human mind must continually and dynamically perform. The second category deals with simulating the processes of making decisions and solving problems in a more abstract and uncontrolled way, much like the unpredictable human mind.

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