◇ 担当教員 : |
新保 仁(Masashi Shimbo / しんぼ まさし)、 能地 宏(Hiroshi Nouji / のうじ ひろし) |
◇ 単位数 :1単位 |
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◇ 選択・必修 :選択 |
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◇ 講義室 :L2 |
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◇ 講義スタイル :講義/公開 |
◇ 授業目的 : |
This course is intended to introduce students to some of the fundamental concepts and techniques in artificial intelligence. |
◇ 授業内容 : |
The topics to be covered include the following:
Lecture 1. Course overview / State space search Lecture 2. Basic search strategies and Dijkstra's algorithm Lecture 3. Heuristic search: A* Lecture 4. Real-time search Lecture 5. Reinforcement learning Lecture 6. Perceptron and neural networks Lecture 7. Computational graph and back propagation Lecture 8. Convolutional and recurrent neural networks
Note: the lectures will be given in English (注: 英語による授業) |
◇ 教科書 : |
None. Lecture slides and hand-outs will be uploaded to the course web page (Follow the link below). 講義スライド・ハンドアウトを講義 web ページ (下のリンク先) で配布します.
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◇ 参考書 : |
1. Stuart Russel and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd ed. Prentice Hall, 2010. ISBN: 0136042597
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◇ 履修条件 : |
Familiarity with graph-theoretic concepts (such as nodes/vertices and edges/arcs) is assumed. Some algorithms are presented in PASCAL-like pseudocode. |
◇ 成績評価 : |
Assignments and quizzes: 100%
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◇ オフィスアワー : |
12:30-13:20 on Tuesdays, or by appointment. Visit Office A703 (Shimbo) or A705 (Noji).
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