By Topic

To Create Intelligent Adaptive Neuro-Controller of Game Opponent from UCT-Created Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
Yiwen Fu ; Int. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China ; Si Yang ; Suoju He ; Jiajian Yang
more authors

Game AI controlled by UCT which achieves excellent performance in computer go can be applied to control non-player characters (NPCs) in video games. While, it is computation intensive algorithm, so applying it to on-line game is not suitable. But data collected from NPC controlled by UCT is able to be utilized to train neuro-controler. Furthermore, neuro-controler is an efficient algorithm due to its capability of extracting knowledge from training data which is generated from UCT. In order to obtain outstanding performance of neuro-controler, training data is a key factor but the structure of neuro-controler is also important. In this paper, the prey and predator game genre of dead- end is utilized as a test-bed, the basic principle of UCT and neuro-controller is drawn, and the effectiveness of their application to game AI development is demonstrated.

Published in:

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on  (Volume:2 )

Date of Conference:

14-16 Aug. 2009