AI: A Modern Approach, Stuart Russell and Peter Norvig.
Additional Readings: Bishop: PRML and other papers.
ESO 211 Data Structures.
The emphasis in this course is on group learning. There will also be a project, involving in-depth learning in a particular area. Lectures will cover some of the core material. Other material will be covered by students in panel discussions. Each of you is also expected to select a project in which you will investigate some topic of current research interest, and you are expected to be able to communicate the key ideas of your project to others in the course.
Written exams : 40%
Course discussions, Homework and Labs : 10-15%
Final Project : 45-50%
(Approx: Proposal: 5%, Presentation 10%, Report 15%, Demo/Oral 20%)
Projects from past years, assignments, solutions, and other details may be seen at Projects
Some projects with a Machine Learning focus may also be relevant: ML Projects
Owing to the high project weightage, project groups will be formed by lottery within the first two weeks of class.
For each topic, there will be one lecture, followed by panel presentations by students.
| Topic | Week | Ref |
| INTRO: AI as Complexity; Managing complexity; agents, symbolic systems | week 1 | ch.1,2 |
| Two themes in AI: Building bodies; building symbols. | week 2 | papers |
| SENSING: Vision - Image Formation, Gradient and Motion cues, Learning Backgrounds, Tracking | week 4 | ch.24, marr.1 |
| ACTION: Robotics - articulated and mobile robots; motion planning, task planning. | week 5 | ch.25 |
| SEARCH and CONSTRAINT PROPAGATION: Game playing | week 6 | ch.3,5,6 |
| LEARNING. Learning Logical Structures: Decision Trees | week 8-9 | ch.18,7 |
| PROBABILISTIC LEARNING: Bayesian networks, Neural Networks and SVMs | week 10-11 | ch.13,14, bishop.1 |