Artificial Intelligence

Numbering Code U-ENG29 39116 LJ12 Year/Term 2021 ・ First semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language Japanese Day/Period Wed.3
Instructor name KANDA TAKAYUKI (Graduate School of Informatics Professor)
Outline and Purpose of the Course This lecture introduces basic technologies of artificial intelligence. Topics will be selected from search, machine learning, and real-world agent.
Course Goals Learning the concept of artificial intelligence and the basic models and algorithms of search, machine learning, and real-world agent.
Schedule and Contents Introduction,1time,Introducing the history of artificial intelligence researches.
Search,3-4times,Introducing breadth-first search, depth-first search, heuristic search, AND/OR-graph search, adversarial search, constraint satisfaction, etc. Applications of search techniques such as computer chess, Sudoku, are also introduced.
Machine Learning,7-8times,Introducing decision tree learning, perceptron, SVM, genetic algorithm, reinforcement learning, deep learning, etc. Applications of machine learning techniques such as data mining are also introduced.
Real-world agent,3-4times,Introducing AI techniques for "uncertain" situation, including basic perception and robotics, and probabilistic reasoning over time. Applications of AI for robotics are also introduced.
Achievement level check,1time,Checking the achievement level
Evaluation Methods and Policy By reports and a final examination.
Course Requirements None
Textbooks Textbooks/References Materials will be distributed.
References, etc. S. Russell and P. Norvig, Artificial Intelligence A Modern Approach (3rd.ed.), Prentice Hall, 2010 isbn{}{9780136042594}.
Courses delivered by Instructors with Practical Work Experience 分類:

A course with practical content delivered by instructors with practical work experience
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