Description

Logistics

Class Days Mondays and Thursdays
Slot AA
Timing 2:00 PM - 3:20 PM
Lecture Room LH 421

Announcements

Topics

The class material will be covered on the white/black board. Slides and reference papers for some of the topics will also be provided. The list is tentative and can be slightly modified as we progress.

The class slides will be uploaded at this link.

S. No. Topics
1. Course Organisation
2. Course Introduction
3. Agent Representation - I
4. Agent Representation - II
5. State Estimation - I
6. State Estimation - II
7. Markov Decision Processes
8. Task Planning
9. Motion Planning
10. RL Introduction
11. Deep Q-Learning
12. Imitation Learning
13. Policy Gradients
14. Actor Critic Methods
15. Monte-Carlo Tree Search
16. Partially-Observable MDPs

References