教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
98-1	129779	演化計算	1	3.0	3	★	高立人 煙淦	電通所	18	0	子四合10/3,24,11/7,14,12/12,19,六9~16上課,餘五789

教學大綱與進度：

教師姓名	煙淦
Email	gyen@okstate.edu
最後更新時間	2009-10-27 12:58:27
課程大綱	本課程概述一些動機源自於生物學的計算方法及知識，並以特定之應用領域來說明演化計算方法，其內容包括： 01. computational intelligence; 02. simulated annealing; 03. introduction to evolutionary computation; 04. genetic algorihms (search operators, search schemes, niching, constraint handling; 05. genetic programming; 06. ant colony system; 07. particle swarm intelligence; 08. evolutionary multiobjective optimization; 09. evolutionary strategy; 10. co-evolution; 11. artificial immune system; 12. memetic algorithm; 13. social based algorithm; 14. learning classifier systems; 15. theoretical analysis
課程進度	01. computational intelligence (10/3) 02. simulated annealing (10/3) 03. introduction to evolutionary computation (10/3) 04. genetic algorihms (search operators, search schemes, niching, constraint handling (10/24) 05. genetic programming (10/24) 06. ant colony system (11/7) 07. particle swarm intelligence (11/7) 08. evolutionary multiobjective optimization (11/7) 09. evolutionary strategy (11/7) 10. co-evolution (11/14) 11. artificial immune system (11/14) 12. memetic algorithm (11/14) 13. social based algorithm (12/12) 14. learning classifier systems (12/12) 15. theoretical analysis (12/12) 16. Presentation (12/19, 12/25, 1/8, 1/15)
評量方式與標準	Homework Assignments on each subject covered: 30% Midterm Project: 30% Final Project: proposal, final report, and oral presentation: 40%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：　 References: Genetic Algorithms in Search, Optimization & Machine Learning, Goldberg, Addison-Wesley, 1989 An Introduction to Genetic Algorithms, Mitchell, MIT, 1996 Ant Colony Optimization, Dorigo and Stutzle, MIT, 2004 Multi-Objective Optimization Using Evolutionary Algorithms, Deb, John Wiley, 2001
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