CS 748: Advances in Intelligent and Learning Agents
(Spring 2021)

(Picture source: https://www.publicdomainpictures.net/pictures/310000/velka/vintage-checkers-game-board.jpg.)


  Shivaram Kalyanakrishnan
  Office: 220, New CSE Building
  Phone: 7704
  E-mail: shivaram@cse.iitb.ac.in

Teaching Assistant

  Santhosh Kumar G.
  E-mail: santhoshkg@iitb.ac.in

Course Description

Artificial intelligence is fast making inroads into various fields, and is indeed influencing our lives in a telling way. This course will accustom students to the state-of-the-art in designing and deploying intelligent and learning agents. The course will build upon the platform laid by CS 747 (Foundations of Intelligent and Learning Agents) to engage students in targeted research and system-building projects.

The course has three main objectives. First, it seeks to impart students the mindset that artificial intelligence and machine learning can substantially benefit real-world problems, and give them the confidence that they can drive this process. Second, the course seeks to develop the students' skills to abstract, analyse, design, implement, evaluate, and iterate while devising solutions. The third objective of the course is to train students to comprehend technical discourse and sharpen their communication skills.

The course is organised in the form of two parallel tracks: lectures (mainly) based on research papers, and a semester-long research project. Topics covered in the lectures will include, among others, multiagent learning, POMDPs, theoretical analysis of MDP planning and learning, representation discovery, exploration, abstraction, animal behaviour, evolutionary algorithms, philosophy of AI, and applications. Students will be provided a short quiz/assignment every week based on the lecture material.

The research project presents an opportunity to students for applying their learning in creative and imaginative ways to understand, build, and analyse systems. Both theoretical and empirical investigations may be undertaken. Students may work alone or in teams. Each team will be guided individually through the phases of the research project, but will share its progress with the class at designated intervals.


Registration is open to students who have passed CS 747 and have secured the instructor's consent (which is decided by a preliminary research proposal).

On-line Mode

Weekly Plan

Details of the web-based interaction, as well as a form for requesting the instructor to call, will be provided on Moodle. In addition, students will be given a feedback form through which they can communicate issues related to the course at any point of time.


There will be 10-12 weekly quizzes, each worth 4–6 marks, and together totaling at least 50 marks. The marks contributed by the quizzes to the grade will be the maximum of the total marks earned in the quizzes and 40.

The research project will carry 60 marks, divided as: 5 marks for an introductory presentation, 5 marks for a proposal, 10 marks for a mid-stage presentation, 10 marks for the final presentation, and 30 marks for the final report. An outstanding research project will bypass the regular evaluation criteria and automatically result in an "AA" grade for the concerned team.

All submissions must be made through Moodle.

Students auditing the course must score 50 or more marks in the course to be awarded an "AU" grade.


Moodle will be the primary course management system. Marks for the assessments will be maintained on the class Moodle page; discussion fora will also be hosted on Moodle. Students who do not have an account on Moodle for the course must send the instructor a request by e-mail, specifying the roll number/employee number for account creation.

Academic Honesty

Students are expected to adhere to the highest standards of integrity and academic honesty. Academic violations, as detailed below, will be dealt with strictly, in accordance with the institute's procedures and disciplinary actions for academic malpractice.

Students are expected to work alone on all the quizzes. They may not share code or consult with classmates (or anybody other than the instructor and TAs) regarding their solutions. Violations will be considered acts of dishonesty.

Students may freely collaborate with their peers on their research, but any assistance received from colleagues must be properly acknowledged in the corresponding presentations and reports.


This page will serve as the primary source of information regarding the course, the schedule, and related announcements. The Moodle page for the course will be used for sharing resources for the lectures and assignments, and also for recording grades.

E-mail is the best means of communicating with the instructor; students must send e-mail to "shivaram@cse.iitb.ac.in" with "[CS748]" in the header.

Texts and References

Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto, 2nd edition, MIT Press, 2018. On-line version.

Artificial Intelligence: Foundations of Computational Agents: David L. Poole and Alan K. Mackworth, 2nd edition, Cambridge University Press, 2017. On-line version.

Selected research papers.


You can also watch all these lectures on the video portal of Swayam Prabha IIT Bombay. For "Department" choose "Computer Science and Engineering"; for Course choose "Advances in Intelligent and Learning Agents"; press "Go".



Slides and videos on this page are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Permission for their use beyond the scope of the license may be sought by writing to shivaram@cse.iitb.ac.in.

Commons License