CS 748: Advances in Intelligent and Learning Agents
(Spring 2020)

(Picture source: "Flatland Challenge" (https://www.aicrowd.com/challenges/flatland-challenge).)


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

Teaching Assistant

  Aditya Sirvaiya
  E-mail: 183050072@iitb.ac.in


Lectures will be held in 101, New CSE Building during Slot 13: 7.00 p.m. – 8.25 p.m. Mondays and Thursdays.

Office hours will be 9.00 a.m. – 10.00 a.m. Tuesdays and 11.00 a.m. – 12.00 p.m. Fridays. Meetings can also be arranged by appointment.

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: class discussions based on research papers, and a semester-long research project. Students will be provided a reading assignment every class, and will be expected to turn in a response summarising their understanding and related observations. Individual responses will be shared with the class, and will guide the class discussion. Topics covered in the reading assignments 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.

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 taken CS 747 and secured BB or a higher grade. Otherwise registration requires the instructor's consent.


Class discussions will carry 45 marks, of which 35 marks will be for written responses to the reading assignments, and 10 marks for contribution to class discussions.

The research project will carry 55 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 25 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.

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 may freely collaborate with their peers, but any assistance received from colleagues must be properly acknowledged in the corresponding presentations and reports. Failure to list any source used in responses to reading assignments will be considered an academic violation.

Reading Material


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.