Date Approved

2-14-2017

Embargo Period

2-15-2017

Document Type

Thesis

Degree Name

MS Computer Science

Department

Computer Science

College

College of Science & Mathematics

First Advisor

Tinkham, Nancy L.

Second Advisor

Hnatyshin, Vasil Y.

Third Advisor

Hristescu, Gabriela

Subject(s)

Artificial intelligence--Computer programs; Board games

Disciplines

Artificial Intelligence and Robotics

Abstract

The game of Arimaa was invented as a challenge to the field of game-playing artificial intelligence, which had grown somewhat haughty after IBM's supercomputer Deep Blue trounced world champion Kasparov at chess. Although Arimaa is simple enough for a child to learn and can be played with an ordinary chess set, existing game-playing algorithms and techniques have had a difficult time rising up to the challenge of defeating the world's best human Arimaa players, mainly due to the game's impressive branching factor. This thesis introduces and analyzes new algorithms and techniques that attempt to recognize similar board states based on relative piece strength in a concentrated area of the board. Using this data, game-playing programs would be able to recognize patterns in order to discern tactics and moves that could lead to victory or defeat in similar situations based on prior experience.

Other Repository URL

http://dissertations.umi.com/rowan:10289

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