An integrated approach to achieving optimal design of computer games

Expert Systems with Applications

Volumn 31, Issue 1, 2006, Pages 145-149

  Hsu, Shang Hwa ^a   Lee, Feng Liang ^a   Wu, Muh Cherng ^a  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

Computer game; Genetic algorithms; Neural networks; Optimization

Indexed keywords

DECISION MAKING; GENETIC ALGORITHMS; INTEGRATION; NEURAL NETWORKS; OPTIMIZATION;

COMPUTER GAME; OPTIMAL DESIGN; TRADE-OFF DECISION;

GAME THEORY;

EID: 33644782768     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2005.09.012     Document Type: Article

References (21)

1. E. Bethke Game development and production 2003 Wordware Publishing Plano, TX
2. M.C. Chen, and S.H. Huang Credit scoring and rejected instances reassigning through evolutionary computation techniques Expert Systems with Applications 24 4 2003 433 441
3. C. Fabricatore, M. Nussbaum, and R. Rosas Playability in action videogames: A qualitative design model Human-Computer Interaction 17 2002 311 368
4. D.E. Goldberg, and K. Deb A comparative analysis of selection schemes used in genetic algorithms G.J.E. Rawlins Foundations of genetic algorithms 1991 Morgan Kaufmann San Mateo, CA 69 93
5. Hsu, S. H., Lee, F. L., & Wu, M. C. (2004). Design for appealing to game buyers. Technical report, IEM, NCTU, Taiwan.
6. K.J. Kim, and I. Han Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index Expert Systems with Applications 19 2 2000 125 132
7. K.J. Kim, and I. Han Application of a hybrid genetic algorithm and neural network approach in activity-based costing Expert Systems with Applications 24 1 2003 73 77
8. R.J. Kuo, and J.A. Chen A decision support system for order selection in electronic commerce based on fuzzy neural network supported by real-coded genetic algorithm Expert Systems with Applications 26 2 2004 141 154
9. S. Lee, H.S. Lee, K.C. Lee, J.W. Choi, and M.H. Lee Performance management of communication networks for computer integrated manufacturing International Journal of Advanced Manufacturing Technology 18 10 2001 764 770
10. S. Li, Z. Wu, and X. Pang Job shop scheduling in real-time cases International Journal of Advanced Manufacturing Technology 2004 10.1007/s00170-003-2051-x
11. T.W. Malone, and M.R. Lepper Making learning fun: A taxonomy of intrinsic motivations for learning R.E. Snow M.J. Farr Aptitude, learning, and instruction, III: Conative and affective process analysis 1987 Lawrence Erlbaum Hillsale, NJ 223 253
12. J.L. Marcelin A metamodel using neural networks and genetic algorithms for an integrated optimal design of mechanisms International Journal of Advanced Manufacturing Technology 24 9-10 2004 708 714
13. Z. Michalewicz Genetic algorithms+data structures=evolution programs 1992 Springer London
14. S.L. Mok, C.K. Kwong, and W.S. Lau A hybrid neural network and genetic algorithm approach to the determination of initial process parameters for injection moulding International Journal of Advanced Manufacturing Technology 18 6 2001 404 409
15. H.B. Qiu, and C.X. Li Conceptual design support system in a collaborative environment for injection moulding International Journal of Advanced Manufacturing Technology 24 1-2 2004 9 15
16. D.E. Rumelhart, G.E. Hinton, and R.J. Williams Learning internal representation by error propagation Parallel and Distributed Processing 1 1986 318 362
17. F. Shi, Z.L. Lou, J.G. Lu, and Y.Q. Zhang Optimisation of plastic injection moulding process with soft computing International Journal of Advanced Manufacturing Technology 21 9 2003 656 661
18. T. Shin, and I. Han Optimal signal multi-resolution by genetic algorithms to support artificial neural networks for exchange-rate forecasting Expert Systems with Applications 18 4 2000 257 269
19. J.C. Su, J.Y. Kao, and Y.S. Tarng Optimization of the electrical discharge machining process using a GA-based neural network International Journal of Advanced Manufacturing Technology 24 1-2 2004 81 90
20. M. Versace, R. Bhatt, O. Hinds, and M. Shiffer Predicting the exchange traded fund DIA with a combination of genetic algorithms and neural networks Expert Systems with Applications 27 3 2004 417 425
21. S.T. Yuan, and S.F. Chen A learning-enabled infrastructure for electronic contracting agents Expert Systems with Applications 21 4 2001 239 256