A comparison of two sigmoidal-type activation functions in video game controller evolution

Tan, Tse Guan and Teo, Jason Tze Wi and Patricia Anthony, (2011) A comparison of two sigmoidal-type activation functions in video game controller evolution. In: 2011 IEEE Conference on Sustainable Utilization Development in Engineering and Technology, STUDENT 2011;Semenyih;20 October 2011through21 October 2011, 20-21 October 2011, Semenyih, Kuala Lumpur, Malaysia.

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Official URL: http://dx.doi.org/10.1109/STUDENT.2011.6089331

Abstract

This paper presents an empirical comparison of two sigmoidal-type activation functions in evolutionary artificial neural network models. They are the log-sigmoid and hyperbolic tangent sigmoid activation functions which were investigated in order for evolving neural network controllers to play a classic video game. A Hill-Climbing Neural Network (HillClimbNet) was developed using the hill-climbing method together with a feedforward neural network to automatically create an intelligent controller that can play the screen-capture of Ms. Pac-man arcade game. The experimental results showed that that the HillClimbNet with log-sigmoid outperforms the HillClimbNet with hyperbolic tangent sigmoid when used in the hidden and output layers of the network when the agent plays the game.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Feed-forward artificial neural network, Hill-climbing, Hyperbolic tangent sigmoid, Log-sigmoid, ms. pac-man
Subjects:?? TK7800-8360 ??
Q Science > QA Mathematics > QA76 Computer software
ID Code:4052
Deposited By:IR Admin
Deposited On:30 Apr 2012 16:32
Last Modified:08 Sep 2014 16:13

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