COL-333/COL-671: Introduction to Artificial Intelligence
Semester I, 2020-21
Description
The course covers foundation of artificial intelligence and is centered around the following themes: intelligent agents and AI, problem solving by search, constraint satisfaction, adversarial search, planning, probabilistic reasoning, decision-making under uncertainty, deep learning, reinforcement learning and applications.
Course Information
- Instructor: Rohan Paul
- Classes: Slot F
- Teaching Assistants: Yatin Nandwani (Head TA), Vikas Upadhyay, Soumen Basu, Atishya Jain, Mayank Singh Chauhan, Siddharth Ranjan, Ashutosh
Announcements
- The course will be conducted in virtual mode.
- The first class was held on Thursday, October 1st over MS Teams.
- The video for lectures is recorded on MS Teams and subsequently made available on Impartus.
- Slides are uploaded before lectures under the Files tab on MS Teams.
- Assignment 1 is released. Submission due on November 6, 2020.
- Queries regarding assignment should be raised on Piazza (information below).
- Minor Exam for COL333 and COL671 to be conducted on November 11, 2020.
- Exam logistics and submission guidelines for Minor Exam on November 11, 2020 are available here.
- Assignment 2 is released.
- Assignment 3 is released.
- Exam logistics and submission guidelines for Major Exam on January 11, 2021 are available here.
Topics
| Week | Topic | Lecture Slides | References |
|---|---|---|---|
| 0 | Course Overview | Slides | -- |
| 1 | Introduction to AI | Slides | AIMA Ch-1 & Ch-2 |
| 2 | Uninformed Search | Slides | AIMA Ch-3 (Sec 3.1 - 3.4) |
| 3 | Informed Search | Slides | AIMA Ch-3 (Sec 3.5 - 3.6) |
| 4 | Local Search | Slides | AIMA Ch-4 (Sec 4.1) |
| 5 | Constraint Satisfaction | Slides | AIMA Ch-6 (Sec 6.1 - 6.4) |
| 6 | Adversarial Search | Slides | AIMA Ch-5 (Sec 5.1 - 5.5) |
| 7 | Quantifying Uncertainty | Slides | AIMA Ch-13 (Sec 13.2 - 13.5) |
| 8 | Probabilistic Reasoning | Slides | AIMA Ch 14 (Sec 14.1 - 14.5.2 (till page 537)) |
| 10 | Probabilistic Reasoning over Time | Slides | AIMA Ch 14 (Sec 15.1 - 15.3) |
| 11 | Markov Decision Processes | Slides | AIMA Ch 17 (Sec 17.1 - 17.3) |
| 12 | Reinforcement Learning | Slides | AIMA Ch 21 (Sec 21.1 - 21.4) |
| 13 | Learning-I: Foundations | Slides | AIMA Ch 21 (Sec 20.1 - 20.2.4) |
| 14 | Learning-II: Neural Networks | Slides | AIMA Ch 18 (18.2/6/7). DL Ch 6 (6.1/2/3/5). |
Assignments
- Assignment 1. Submission due on November 6, 2020.
- Assignment 2. Submission due on December 9, 2020.
- Assignment 3. Submission due on December 27, 2020.
Piazza
- Queries if any should be raised on Piazza. Enrol on piazza.com/iit_delhi for the course Fall 2020 term of COL 333: Artificial Intelligence using access code: col333.
- Bonus (2%) for class participation on Piazza (discretionary).
References
- Primary Reference: Artificial intelligence: a modern approach. Russell, Stuart J., and Peter Norvig. Link [AIMA]
Resources
- Reinforcement Learning (Second Edition). Richard Sutton and Andrew Barto. MIT Press. 2018. Online [SB]
- Deep Learning. Ian Goodfellow, Yoshua Bengio and Aaron Courville. Online [DL]
- Previous course offerings by Prof. Mausam. Link
Evaluations with Tentative Weighting
- Exams: Minor (20%) and Major (38%)
- Assignments (42%)
Other Criteria
- Audit Pass (NP) criteria: 30% marks as per institute guidelines.
- Pass requirement for credit: 30% marks as per institute guidelines.
- Attendance: recommended but not a criterion for evaluation.
Honor Code
- Cases of copying an assignment will be awarded a penalty of at least -10 (absolute) and an F grade will be provided.
- Institute guidelines will apply in handling cases of copying. Department guidelines for checking plagiarism will apply.