Date of Award
2011
Document Type
Thesis
Publisher
Edith Cowan University
Degree Name
Bachelor of Computer Science Honours
School
School of Computer and Security Science
Faculty
Faculty of Computing, Health and Science
First Supervisor
Associate Professor Philip Hingston
Second Supervisor
Dr Martin Masek
Abstract
This study has investigated novel Automated Red Teaming methods that support replanning. Traditional Automated Red Teaming (ART) approaches usually use evolutionary computing methods for evolving plans using simulations. A drawback of this method is the inability to change a team’s strategy part way through a simulation. This study focussed on a Monte-Carlo Tree Search (MCTS) method in an ART environment that supports re-planning to lead to better strategy decisions and a higher average score
Recommended Citation
Beard, D. (2011). Enhancing automated red teaming with Monte Carlo Tree Search. Edith Cowan University. https://ro.ecu.edu.au/theses_hons/36