一、課程說明 (Course Desc<x>ription) 
<br>This course provides an introduction to the algorithms, theory, and application 
<br>of evolutionary computation geared towards the students who are interested in 
<br>development and/or application of the subject. Topics in algorithms and theory 
<br>include genetic algorithms, evolution strategies, genetic programming, parameter 
<br>setting and analysis. Topics in application include optimization, constraint 
<br>handling, machine learning, and multi-ob<x>jective optimization.
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<br>二、指定用書 (Text Book) 
<br>A.E. Eiben and J.E. Smith, Introduction to Evolutionary Computing, Springer 
<br>Verlag, 2003/2010.
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<br>三、參考書籍 (References)
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<br>四、教學方式 (Teaching Method)
<br>Lecture slides and blackboard teaching
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<br>五、教學進度 (Syllabus)
<br>1. Introduction
<br>2. What is an Evolutionary Algorithm?
<br>3. Genetic Algorithms
<br>4. Evolution Strategies
<br>5. Genetic Programming
<br>6. Multi-ob<x>jective Evolutionary Algorithms
<br>7. Working with EAs
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<br>六、成績考核 (Evaluation) 
<br>Assignment: 30%
<br>Midterm Exam: 40%
<br>Project: 30%
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<br>七、可連結之網頁位址
<br>eeclass
<br>