COL-864: Special Topics in Artificial Intelligence
Planning and Estimation for Autonomous Systems

Credits: (3-0-0)

Holi Term 2021

Description

Planning and estimation are central to autonomous systems operating in the real world. This course will cover the concepts, principles and methods for intelligent decision-making with imperfect or uncertain knowledge. Students will develop an understanding of how different planning and learning techniques are usefulin problem domains where robots or other embodied-AI agents are deployed. Introduction to Artificial Intelligence (COL333-671) or Introduction to Machine Learning (COL774 or equivalent). Programming proficiency and knowledge of probabilistic models, basic deep learning, basic search algorithms, logic and probability will be an advantage.

Announcements

Course Information

Lectures

S. No. Topic Class Material
1 Course Organization Slides
2 Course Introduction Slides
3 Agent Representation Slides
4 Planning Motions Slides
5 State Estimation - I Slides
6 State Estimation - II Slides
7 Planning - A* Search Slides
8 Task Planning Slides
9 Markov Decision Processes Slides
10 Model-Based RL Slides
11 Model-Free RL - II Slides
12 DQN and Policy Gradients Slides
13 Partially-Obervable MDPs Slides

Revised Pass Criterion

Revised Assignment II Submission

Assignments

Examination

References

Background Reading Material

Learning outcomes

At the end of the course students will be able to: model autonomous systems as AI agents, formulate/solve relevant planning/estimation tasks. Further, students will gain insights in the computational challenges arising from uncertainty and how to incorporate recent learning-based methods decision-making algorithms.