4190.408 Artificial Intelligence (Spring 2019)
School of Computer Science and Engineering, Seoul National University
- Instructor: Prof. Byoung-Tak Zhang
- TA: Seong-ho Choi & Yu-won Jang
- TA E-Mail: ta4ai19s@gmail.com
- Classroom: 302-209
- Time: Tue & Thu 11:00–12:15
Objectives
- To study a wide range of artificial intelligence theory, techniques and systems about machines that behave and think like people.
- To understand concepts, models, and algorithms to develop intelligent agents such as navigation, reasoning, planning, knowledge representation, decision making, learning, visual and language.
- To learn and practice key technologies of artificial intelligence such as empirical search, Bayesian network, Hidden Markov network, and reinforcement learning.
Textbook
- Artificial Intelligence: A Modern Approach, S. Russell & P. Norvig, Pearson, 2010
References
- 장병탁, 장교수의 딥러닝, 홍릉과학출판사, 2017
Evaluation
- Mid / Final Terms: 60%
- Project: 20%
- Homework & Practice: 20%
Projects
- Project 1: Analysis of AlphaGo
- Project 2: Hidden Markov Models
Announcements
- (3/5) Lecture schedule was updated with lecture slides.
- (3/11) Homework 1 posted. Due date: 3/28.
- (3/12) Homework 1 updated with Chapter 3. Due date: 3/28.
- (3/21) Project 1 announced.
- (4/2) Homework 2 posted. Due date: 4/18.
- (5/11) Project 2 posted. Due date: 6/10.
- (5/16) Homework 3 posted. Due date: 6/4.
Lecture Schedule
| Week | Date | Topics |
|---|---|---|
| 1 | 3/5 (Tue) | History (Ch 1. Introduction) |
| 1 | 3/7 (Thu) | Agents (Ch 2. Intelligent Agents) |
| 2 | 3/12 (Tue) | Search 1 (Ch 3. Solving Problems by Searching) |
| 2 | 3/14 (Thu) | Search 2 (Ch 4. Beyond Classical Search) |
| 3 | 3/19 (Tue) | Search 3 (Ch 5. Adversarial Search) |
| 3 | 3/21 (Thu) | Practice Session 1 & Project 1 Announcement |
| 4 | 3/26 (Tue) | Logical Reasoning 1 (Ch 7. Logical Agents) |
| 4 | 3/28 (Thu) | Logical Reasoning 2 (Ch 8. First-Order Logic, Ch 9. Inference in First-Order Logic) |
| 5 | 4/2 (Tue) | Practice Session 2 |
| 5 | 4/4 (Thu) | Probabilistic Reasoning 1 (Ch 13. Quantifying Uncertainty) |
| 6 | 4/9 (Tue) | Probabilistic Reasoning 2 (Ch 14. Probabilistic Reasoning, Bayesian Networks) |
| 6 | 4/11 (Thu) | Probabilistic Reasoning 3 (Ch 14. Exact Inference in BNs) |
| 7 | 4/16 (Tue) | Probabilistic Reasoning 4 (Ch 14. Approximate Inference in BNs) |
| 7 | 4/18 (Thu) | Review and Discussion |
| 8 | 4/23 (Tue) | Mid Term |
| 8 | 4/25 (Thu) | Practice Session 3 (Hidden Markov Models) & Project 2 Announcement |
| 9 | 4/30 (Tue) | Temporal Reasoning 1 (Ch 15. Probabilistic Reasoning over Time, HMM) |
| 9 | 5/2 (Thu) | Temporal Reasoning 2 (Ch 15. Kalman Filters, DBN, Particle Filters) |
| 10 | 5/7 (Tue) | Temporal Reasoning 3 (Ch 15. Dynamic Bayesian Networks) |
| 10 | 5/9 (Thu) | Learning Probabilistic Models 1 (Ch 20. Learning Probabilistic Models) |
| 11 | 5/14 (Tue) | Neural Networks (Ch 18.7. Artificial Neural Networks) |
| 11 | 5/16 (Thu) | Practice Session 4 |
| 12 | 5/21 (Tue) | Neural Networks (Ch 18.7. Artificial Neural Networks) |
| 12 | 5/23 (Thu) | Natural Language (Ch 22–23. Natural Language Processing) |
| 13 | 5/28 (Tue) | Vision (Ch 24. Perception) |
| 13 | 5/30 (Thu) | Robotics (Ch 25. Robotics) |
| 14 | 6/4 (Tue) | Final Exam |
| 14 | 6/6 (Thu) | Holiday |
| 15 | 6/11 (Tue) | Project 2 Poster Presentation |
| 15 | 6/13 (Thu) | Future of AI (Discussion) |