Course Description
Fundamental issues in intelligent systems. Knowledge representation and mechanisms of reasoning. Search and constraint satisfaction. Agents. Application areas of AI and current topics. Students will learn basic concepts of artificial intelligence and get some hands on experience to solve real-life problems. Python will be used for all the assignments.
Textbook
B1. Artificial Intelligence: A Modern Approach
B2. Convex Optimization (optional)
B3. Applied Mathematical Programming (optional)
Communication
All written communication should be directed though Google Classroom. You can post publicly or privately depending on your preference. Emails won’t be responded to.
Schedule
| Date | Lecture | Misc |
|---|---|---|
| Problem Solving and Search | ||
| Tue Jan 07 | Introduction To AI | Ch 1 and Ch 2 |
| Thu Jan 09 | Uninformed Search - I | Ch 3.1-3.4 |
| Tue Jan 14 | Uninformed Search - II | Ch 3.1-3.4 |
| Thu Jan 16 | Informed and Local Search | Ch 3.5-3.7, 4.1-4.2 |
| Tue Jan 21 | Constraint Satisfaction - I | Ch 6 |
| Thu Jan 23 | Constraint Satisfaction - II | Ch 6 |
| Tue Jan 28 | No-class (instructor out-of-office) | |
| Thu Jan 30 | Adversarial Search - I | Ch. 5.1-5.3 |
| Tue Feb 04 | Adversarial Search - II | Ch. 5.1-5.3 |
| Optimization | ||
| Thu Feb 06 | Linear Programming | Ch 2 and 4 of B3 |
| Tue Feb 11 | Integer Programming | Ch 9 of B3 |
| Thu Feb 13 | Convex Optimization - I | Ch 1 and 4 of B2 |
| Tue Feb 18 | Convex Optimization - II | Ch 1 and 4 of B2 |
| Sequential Decision Making | ||
| Thu Feb 20 | Markov Decision Processes - I | Ch 17.1-17.3 |
| Tue Feb 25 | Markov Decision Processes - II | Ch 17.1-17.3 |
| Thu Feb 27 | Midterm Exam | |
| Tue Mar 03 | Spring Break; No Class | |
| Thu Mar 05 | Spring Break; No Class | |
| Tue Mar 10 | Reinforcement Learning - I | Ch 21 |
| Thu Mar 12 | Reinforcement Learning - II | Ch 21 |
| Tue Mar 17 | Reinforcement Learning - III | Ch 21 |
| Probabilistic Reasoning | ||
| Thu Mar 19 | Introduction to Probability | Ch 13.1-13.5 |
| Tue Mar 24 | Bayesian Networks: Representation | Ch 14.1-14.2, 14.4 |
| Thu Mar 26 | Bayesian Networks: Independence | Ch 14.3 |
| Tue Mar 31 | Bayesian Networks: Inference | Ch 14.4 |
| Thu Apr 02 | Bayesian Networks: Sampling | Ch 14.4-14.5 |
| Tue Apr 07 | Decision Networks | Ch 16.5-16.6 |
| Thu Apr 09 | Hidden Markov Models | Ch 15.2, 15.5 |
| Tue Apr 14 | Particle Filtering | Ch 15.2, 15.6 |
| Assorted Topics | ||
| Thu Apr 16 | AI for Humans | Ch 18.8 |
| Tue Apr 21 | AI Applications: Perception, Robotics, Language | - |
| Thu Apr 23 | Final Review | |
| Wed May 01 | Final Exam (7:45am-9:45am) |