シラバス参照
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シラバス参照
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| 講義概要/Course Information |
| 科目基礎情報/General Information |
| 授業科目名 /Course title (Japanese) |
Topics in Informatics Ⅰ（Evolutionary Computation）（学域） | ||
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| 英文授業科目名 /Course title (English) |
Topics in Informatics Ⅰ（Evolutionary Computation） | ||
| 科目番号 /Code |
INT004a INT004b INT004e | ||
| 開講年度 /Academic year |
2020年度 | 開講年次 /Year offered |
3/4 |
| 開講学期 /Semester(s) offered |
後学期 | 開講コース・課程 /Faculty offering the course |
情報理工学域 |
| 授業の方法 /Teaching method |
講義 | 単位数 /Credits |
2 |
| 科目区分 /Category |
専門科目 | ||
| 開講学科・専攻 /Cluster/Department |
Ⅰ類/Ⅱ類 | ||
| 担当教員名 /Lecturer(s) |
佐藤 寛之 | ||
| 居室 /Office |
W6-205 | ||
| 公開E-Mail |
h.sato@uec.ac.jp | ||
| 授業関連Webページ /Course website |
WebClass | ||
| 更新日 /Last updated |
2020/03/02 12:07:55 | 更新状況 /Update status |
公開中 /now open to public |
| 講義情報/Course Description |
| 主題および 達成目標 /Topic and goals |
Evolutionary computation is a bio-inspired computation methodology and categorized as a part of computational intelligence. Evolutionary computation treats information as genes of organisms, and evolve it inside the computer. The primary usage of evolutionary computation is optimization. As representative industrial applications, the front nose design of the Shinkansen N700 and the wing design of the Mitsubishi regional jet (MRJ) were optimized by evolutionary computation. Evolutionary optimization can be applied even if the characteristic of the target optimization problem is unknown. This course provides lectures of evolutionary algorithms from classic to the latest ones, types of optimization problems, their handling methods in evolutionary algorithms, and implementation techniques. The goals of the class are to be able to recognize the types of optimization problems, select appropriate evolutionary algorithms, and implement one of these algorithms. |
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| 前もって履修 しておくべき科目 /Prerequisites |
The course has computer exercises involving programming. Students need to know at least one programming language. |
| 前もって履修しておくこ とが望ましい科目 /Recommended prerequisites and preparation |
Computer literacy, Fundamental programming |
| 教科書等 /Course textbooks and materials |
Materials are distributed by using WebClass system. |
| 授業内容と その進め方 /Course outline and weekly schedule |
1. Introduction to Evolutionary Computation 2. Optimization Problems 3. MATLAB Programming 4. Hill Climbing 5. Genetic Algorithms 6. Evolutionary Programming 7. Evolution Strategies 8. Genetic Programming 9. Evolutionary Algorithm Variations 10. Simulated Annealing 11. Particle Swarm Optimization 12. Differential Evolution 13. Estimation of Distribution Algorithm 14. Evolutionary Multi-objective Optimization 15. Other Applications and Futures of Evolutionary Computation |
| 実務経験を活かした 授業内容 (実務経験内容も含む) /Course content utilizing practical experience |
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| 授業時間外の学習 （予習・復習等） /Preparation and review outside class |
Review and computer exercises are needed after the weekly class. |
| 成績評価方法 および評価基準 （最低達成基準を含む） /Evaluation and grading |
Report submissions related to computer exercises are required. The reports are scored, and the evaluation is decided by the followings (100 points maximum). S: >= 90 points A: >= 80 points B: >= 70 points C: >= 60 points D: <60 points |
| オフィスアワー： 授業相談 /Office hours |
Tuesday, 10:40-12:10. Please make sure to make an appointment by e-mail before visiting the lecturer. |
| 学生へのメッセージ /Message for students |
N/A |
| その他 /Others |
N/A |
| キーワード /Keyword(s) |
Evolutionary computation, evolutionary algorithm, optimization, computational intelligence |