Application research of unsupervised neural networks in game development
Jin Gao · Computer Engineering and Applications Journal · 2008
This paper has resolved obstacle avoidance problem in game using unsupervised Neural Networks.This unsupervised mechanism is made by Genetic Algorithm,which has improved the weights of the Neural Networks through optimizing the fitness,finally,the Neural Networks can get the outputs with best fitness.Sensors are simulated by 5 line segments that radiate outward from the agent body,the agent can sense the game environment by the 5 sensors.After iterating for 768 times,average fitness and best fitness of the population have been improved quickly,the ratio of avoiding successfully has been improved from 12.5% to 85%.