Title :
A simple heuristic search method for the automatic generation of neural-based game artificial intelligence architectures in Ms. Pac-Man
Author :
Tan, Tse Guan ; Teo, Jason ; Anthony, Philip
Author_Institution :
Evolutionary Comput. Lab., Univ. Malaysia Sabah, Kota Kinabalu, Malaysia
Abstract :
In this work, we develop a game controller called HillClimbingNet (Hill-Climbing Neural Network) for playing Ms. Pac-man that combines the hill-climbing concept and simple feedforward neural network. The computational experiments have been conducted to evaluate and compare the proposed algorithm against Random Direction (RandDir) and Random Neural Network (RandNet) systems. According to the simulation results, HillClimbingNet has achieved an average score of 6290, but only 439 and 735 on the RandDir and RandNet, respectively. HillClimbingNet has a very good performance.
Keywords :
computer games; evolutionary computation; feedforward neural nets; heuristic programming; neural nets; stochastic games; unsupervised learning; Ms. Pac-man; RandDir; RandNet; artificial intelligence architecture; automatic generation; feedforward neural network; game controller; heuristic search method; hill-climbing neural network; neural-based game; random direction; random neural network system; Artificial neural networks; Feedforward neural networks; Games; Intelligent systems; Search methods; Unsupervised learning;
Conference_Titel :
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7165-2
DOI :
10.1109/ISSPA.2010.5605407
