This project was designed to compare and contrast Evolving Behavior Trees (EBTs) with NeuroEvolution of Augmenting Topologies (NEAT), a Genetic Algorithm for the evolution of Artificial Neural Networks. We used Super Mario Bros. as a benchmark to compare these two techniques. The results showed that NEAT had a slightly higher maximum fitness while performing poorly in all other comparisons. EBTs performed strongly in rise time, evolution time, generalization, and complexity.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Kuhn, Karl Jansen
• Foley, Ross Patrick

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042815-140233

Advisor

• Chernova, Sonia

Year

• 2015

Date created

• 2015-04-28

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright