Referenced Items are not available for this document.
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.
Published in:
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Date of Conference: 10-13 May 2010
- Page(s):
- 753 - 756
- Print ISBN:
- 978-1-4244-7165-2
- INSPEC Accession Number:
- 11596612
- Conference Location :
- Kuala Lumpur
- Digital Object Identifier :
- 10.1109/ISSPA.2010.5605407
- Product Type:
- Conference Publications
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