Course title
P05302003
Introduction of Artificial Intelligence

aiba akira Click to show questionnaire result at 2018
Course description
Ai:Artificial Intelligence is a study of human intelligence and realizing it on computers.
This class will be focused on "searching" which is one of the main topics in AI with making programs in symbol processing language Lisp.
Purpose of class
Students will learn basics of AI, and acquire skills of programming mainly on searching in Lisp.
Goals and objectives
  1. Acquiring basic knowledge on AI, and understanding its background.
  2. Making programs based on acquired knowledge.
  3. Acquiring the way to learn further topics in AI.
Language
Japanese
Class schedule

Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Overview of the class
What is AI
History of AI
Aims of AI
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
2. On "searching"
What is "searching"
Representation of problems
State transition and search tree
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
3. Basic search strategy 1
Depth-first search
Examples of depth-first search
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
4. Basic search strategy 2
Breadth-first search
Examples of breadth-first search
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
5. Basic search strategy 3
State transition and finite automaton
Search Strategies
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
6. Trial and error by evaluation
1
Evaluation of states and search passes
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
7. Trial and error by evaluation 2
Evaluation of costs
Hill climbing method
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
8. Mid-team exam Reviewing exam. 45minutes
9. Trial and error by evaluation 3
Best-path search 1
Combinatorial explosion
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
10. Trial and error by evaluation 4
Best-path search 2
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
11. Trial and error by evaluation 5
And-Or tree and searching in games 1
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
12. Trial and error by evaluation 6
And-Or tree and searching in games 2
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
13. Knowledge representation and processing
Knowledge representation by Logic
Reasoning by resolution
Negation and closed world assumption
Reviewing contents of the class, finishing quiz and complete programs. 30minutes
14. Final exam Reviewing final exam 45minutes
Total. - - 450minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

Quiz Mid-term exam Final exam Total.
1. 10% 10% 20% 40%
2. 5% 5% 5% 15%
3. 5% 5% 5% 15%
4. 5% 5% 5% 15%
5. 5% 5% 5% 15%
Total. 30% 30% 40% -
Evaluation method and criteria
Weighted average of Quiz, Mid-term exam, and Final exam.
Students who can understand problems in Quiz will be 70%
Textbooks and reference materials
Not specified.
Prerequisites
Taking classes of "Discrete Mathematics", and "Data structure and Algorithms" will be strongly recommended.
Office hours and How to contact professors for questions
  • Tuesday, 12:30 - 13:00
Relation to the environment
Non-environment-related course
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicatable
N/A N/A
Last modified : Thu Mar 21 14:52:35 JST 2019