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2020年度


31691005 

△Advanced Nature-Inspired Computing(E)
Advanced Nature-Inspired Computing (E)
2単位/Unit  秋学期/Fall  京田辺/Kyotanabe  講義/Lecture

  IVAN TANEV

<概要/Course Content Summary>

This course presents a collection of ‘nature-inspired’ heuristic optimization techniques for applicable for computationally ‘hard’ problems, e.g. evolutionary computations (genetic algorithms, genetic programming, evolutionary strategies), artificial immune systems, swarm intelligence and neurocomputing.

<到達目標/Goals,Aims>

The overall teaching objective is to ensure that students are able to approach nature-inspired solutions to various computationally ‘hard’ tasks requiring an optimization, search, design, planning and control.

<授業計画/Schedule>

(実施回/
Week)
(内容/
Contents)
(授業時間外の学習/
Assignments)
(実施回/ Week) (内容/ Contents) Introduction to Nature-inspired Computing  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Bionics  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Evolutionary Computing: Genetic Algorithms (GA), Part 1  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Evolutionary Computing: Genetic Algorithms (GA), Part 2  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Evolutionary Computing: Genetic Programming (GP), Part 1  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Evolutionary Computing: Genetic Programming (GP), Part 2  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Evolutionary Robotics  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) (内容/ Contents) Summary of the First Half of the Course  (授業時間外の学習/ Assignments) Midterm Evaluation 
(実施回/ Week) (内容/ Contents) Software Agents, Part 1  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) 10  (内容/ Contents) Software Agents, Part 2  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) 11  (内容/ Contents) Introduction to Machine Learning. 
Learning from Observation. Decision Tree Learning, Part 1 
(授業時間外の学習/ Assignments) Review 
(実施回/ Week) 12  (内容/ Contents) Introduction to Machine Learning. 
Learning from Observation. Decision Tree Learning, Part 2 
(授業時間外の学習/ Assignments) Review 
(実施回/ Week) 13  (内容/ Contents) Cellular Automata  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) 14  (内容/ Contents) Neurocomputing: Artificial Neural Networks  (授業時間外の学習/ Assignments) Review 
(実施回/ Week) 15  (内容/ Contents) Summary and Conclusion  (授業時間外の学習/ Assignments) Final Evaluation 

<成績評価基準/Evaluation Criteria>

Mid-term report  50%   
End-term report  50%   

 

<成績評価結果/Results of assessment>   成績評価の見方について/Notes for assessment

    

登録者数

成績評価(%)

評点
平均値

備考

A+ A B+ B C+ C F
27 22.2 14.8 11.1 11.1 11.1 0.0 29.6 0.0 2.6 *

<テキスト/Textbook>

Albert Y. Zomaya (Editor) , Hondbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies ,  1 edition (January 10, 2006) .   (Springer, 2006) ,  736 pages .  ISBN-13: 978-0387405322 

 

<参考文献/Reference Book>

Leandro N. de Castro (Editor), Fernando J. Von Zuben (Editor) , Recent Developments in Biologically Inspired Computing ,  22-Mar-05 .   (Idea Group Publishing, 2005) ,  439 pages .  ISBN-13: 978-1591403128 

 

 

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