Date of Award
2010
Document Type
Thesis
Degree Name
Bachelors
Department
Natural Sciences
First Advisor
Henckell, Karsten
Keywords
Neural Network, General Algorithm, Video Game
Area of Concentration
Computer Science
Abstract
A branch of Artificial Intelligence known as natural computing, which proposes learning algorithms based on naturally occurring processes such as natural selection and biological processes such as neural networks, has been shown to be capable of learning and generalization of complex problems. This thesis evaluates two such biologically motivated techniques � temporal difference learning, which learns by reinforcement, and a genetic algorithm, which learns by natural selection � by teaching a neural network to play the classic arcade game Pac-Man. A replica of Pac-Man was created using the Python programming language, and networks trained with temporal difference learning, a genetic algorithm, and a combination of the two, each for 32 hours, were shown to exhibit concrete strategies and a significant improvement compared to a random solution.
Recommended Citation
Goldsmith, Daniel Matthew, "Another One Bites the Dot Teaching a Neural Network to Play Pac-Man Using Biologically Motivated Learning Techniques" (2010). Theses & ETDs. 4265.
https://digitalcommons.ncf.edu/theses_etds/4265