Intelligent Systems |
YAMANE, Ken |
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【 Informatics Science〈Correspondence Course〉(Master's Degree Program)･full year】
18-3-1724-3192 |
| １． |
Outline |
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We overview classical artificial intelligence and discuss its limitations. Also, this course deals with the following topics: soft-computing, pattern recognition and machine learning.
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| ２． |
Objectives |
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The aim of the course is to learn fundamental concepts and techniques of intelligent systems.
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| １． |
Outline |
|
We overview classical artificial intelligence and discuss its limitations. Also, this course deals with the following topics: soft-computing, pattern recognition and machine learning.
|
| ２． |
Objectives |
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The aim of the course is to learn fundamental concepts and techniques of intelligent systems.
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| ３． |
Grading Policy |
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Evaluated with reports.
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| ４． |
Textbook and Reference |
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No textbook is used.
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Requirements (Assignments) |
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Students should use E-mail and LMS.
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Note |
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| ７． |
Schedule |
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| １. Introduction |
| ２. Classical artificial intelligent I |
| ３. Classical artificial intelligent II |
| ４. Classical artificial intelligent III |
| ５. Limits of AI |
| ６. Subsumption architecture |
| ７. Soft-computing I |
| ８. Soft-computing II |
| ９. Soft-computing III |
| 10. Soft-computing IV |
| 11. Pattern recognition and machine learning I |
| 12. Pattern recognition and machine learning II |
| 13. Reinforcement learning I |
| 14. Reinforcement learning II |
| 15. Summary |
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