Search

Fall 2023

Wang, Jiuqi

In this thesis, we investigate applying deep learning techniques to learn the win-loss-draw results contained in the databases of the checkers-playing program CHINOOK. Our initial objectives were to (1) compare a deep-learning-based compression scheme versus the custom algorithm used in CHINOOK,...

Fall 2014

Valenzano, Richard Anthony

Heuristic search has been shown to be an effective way to solve state-space problems. While many heuristic search techniques are guaranteed to find the best solution, these are often not feasible given practical resource requirements. In such cases, it is necessary to sacrifice solution...

Spring 2010

KIRCI, MESUT

Domain-independent feature learning is a hard problem. This is reflected by lack of broad research in the area. The goal of General Game Playing (GGP) can be described as designing computer programs that can play a variety of games given only a logical game description. Any learning has to be...

Fall 2011

Metcalf, Adam

Pinball is fast-paced arcade-style game of which the origins date back hundreds of years. Game playing robots exist for billiards, foosball, and soccer and each have their own unique challenges. The speed that balls move in pinball machines requires that players have quick reactions. We created...

Spring 2010

Shafiei Khadem, Mohammad

General Game Playing (GGP) deals with the design of players that are able to play any discrete, deterministic, complete information games. For many games like chess, designers develop a player using a specially designed algorithm and tune all the features of the algorithm to play the game as good...

Fall 2009

Valenzano, Richard

Many single-agent search algorithms have parameters that need to be tuned. Although settings found by offline tuning will exhibit strong average performance, properly selecting parameter settings for each problem can result in substantially reduced search effort. We consider the use of...