Self-synthesized controllers for tower defense game using genetic programming

Author

Leow Chin Leong ; Gan Kim Soon ; Tan Tse Guan ; Chin Kim On ; Alfred, Rayner ; Anthony, Philip

Author_Institution

Center of Excellent in Semantic Agents, Univ. Malaysia Sabah, Kota Kinabalu, Malaysia

fYear

2013

fDate

Nov. 29 2013-Dec. 1 2013

Firstpage

487

Lastpage

492

Abstract

In this paper, we describe the results of implementing Genetic Programming (GP) using two different Artificial Neural Networks (ANN) topologies in a customized Tower Defense (TD) games. The ANNs used are (1) Feed-forward Neural Network (FFNN) and (2) Elman-Recurrent Neural Network (ERNN). TD game is one of the strategy game genres. Players are required to build towers in order to prevent the creeps from reaching their bases. Lives will be deducted if any creeps manage to reach the base. In this research, a map will be designed. The AI method used will self-synthesize and analyze the level of difficulty of the designed map. The GP acts as a tuner of the weights in ANNs. The ANNs will act as players to block the creeps from reaching the base. The map will then be evaluated by the ANNs in the testing phase. Our findings showed that GP works well with ERNN compared to GP with FFNN.

Keywords

artificial intelligence; computer games; control engineering computing; feedforward neural nets; genetic algorithms; recurrent neural nets; AI method; ANN topologies; ERNN; Elman-recurrent neural network; FFNN; artificial neural networks; feedforward neural network; genetic programming; self-synthesized controllers; tower defense game; Artificial intelligence; Artificial neural networks; Biological cells; Creep; Games; Neurons; Poles and towers; Artificial Neural Network (ANN); Elman-Recurrent Neural Network (ERNN); Feed-forward Neural Network (FFNN); Genetic Programming (GP); Tower Defense (TD) Game;

fLanguage

English

Publisher

ieee

Conference_Titel

Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on

Conference_Location

Mindeb

Print_ISBN

978-1-4799-1506-4

Type

conf

DOI

10.1109/ICCSCE.2013.6720014

Filename

6720014