人工知能:探索とマイニング (130012) Artificial Intelligence: Search and Mining (130012)
 
◇ 担当教員 Instructor : 新保 仁(Masashi Shimbo / しんぼ まさし)
◇ 単位数 Credits : 1単位 ◇ 選択・必修 Required/Elective : 選択 ◇ 講義室 Room : L2
◇ 講義スタイル Style : 講義/公開
◇ 開講時期 Quarter : Ⅰ期 火曜2限

◇ 授業目的 Course goals : This course is intended to introduce students to fundamental concepts and techniques in AI heuristic search, and in data mining.
◇ 授業内容 Course description : The topics to be covered include the following:

Lecture 1. Course overview / Typology of AI search
Lecture 2. Uninformed search (breadth-first and depth-first searches)
Lecture 3. Dijkstra's algorithm
Lecture 4. Heuristic search: A*
Lecture 5. IDA* and other heuristic search methods
Lecture 6. Frequent Itemset Mining
Lecture 7. Sequence Mining
Lecture 8. Graph Mining

Note: the lectures will be given in English (注: 英語による授業)

◇ 教科書 Textbook : 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.
◇ 参考書 Reference materials : 1. Stuart Russel and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd ed. Prentice Hall, 2010. ISBN: 0136042597
2. Anand Rajaraman, Jeffrey David Ullman, and Jure Leskovec. Mining of Massive Datasets, 2nd ed. Cambridge University Press, 2014. ISBN-13: 9781107015357
◇ 履修条件 Prerequisites : 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 Grading : Assignments: 100%
◇ オフィスアワー Office Hours : 12:30-13:20 on Tuesdays (Room A703), or by appointment
◇ 講義関連URL URL :
Course web page | 講義ホームページ
◇ 配布資料 Handouts : 現在、配布資料はありません。