Reinforcement learning to control a commander for capture the flag

Ivanovic, J, Zambetta, F, Li, X and Rivera Villicana, J 2014, 'Reinforcement learning to control a commander for capture the flag', in G. Rudolph and M. Preuss (ed.) Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games (CIG), Dortmund, Germany, 26 - 29 August 2014, pp. 161-168.


Document type: Conference Paper
Collection: Conference Papers

Title Reinforcement learning to control a commander for capture the flag
Author(s) Ivanovic, J
Zambetta, F
Li, X
Rivera Villicana, J
Year 2014
Conference name CIG 2014
Conference location Dortmund, Germany
Conference dates 26 - 29 August 2014
Proceedings title Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games (CIG)
Editor(s) G. Rudolph and M. Preuss
Publisher IEEE
Place of publication United States
Start page 161
End page 168
Total pages 8
Abstract Capture the flag (CTF) is a popular game mode for many blockbuster games. Agents in these games struggle against the players who learn to adapt to their strategies leading to the players dissatisfaction. We present our work on using Reinforcement Learning (RL) algorithms to learn a controller of a commander in the AI Sandbox platform, a flexible simulation environment which allows users across the world to participate in a variety of challenges and competitive games. As a result of building an RL controller for a commander we found that performance varies significantly across opponents, maps and team sizes, where the RL controller shows adequate performance in a subset of the games played and struggles in others.
Subjects Adaptive Agents and Intelligent Robotics
Virtual Reality and Related Simulation
Keyword(s) Capture the flag
DOI - identifier 10.1109/CIG.2014.6932880
Copyright notice © 2014 IEEE
ISBN 9781479935482
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 1 times in Scopus Article | Citations
Altmetric details:
Access Statistics: 137 Abstract Views  -  Detailed Statistics
Created: Fri, 17 Apr 2015, 15:25:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us