CS6380: Artificial Intelligence

Jul - Nov 2026

Course Information

Offered for: BTech, MTech, MS, PhD
Instructor: Pulkit Verma
Teaching Assistants:
Jignasa Bhunia (cs26s003@smail.iitm.ac.in)
Dhrubajyoti Giri (cs26m013@smail.iitm.ac.in)
Raju Kumar Gupta (cs26m034@smail.iitm.ac.in)
Ravijyotisna Pachauri (cs25m040@smail.iitm.ac.in)
Dudekula Abdul Rahiman (cs26s001@smail.iitm.ac.in)
Harshul Sharma (cs25m024@smail.iitm.ac.in)
Room: CSB 15, CSB (Ground floor)
Class Times:
Monday: 02:00 - 03:15 PM
Tuesday: 03:30 - 04:45 PM
Thursday: 05:00 - 05:50 PM
Office Hours:
Monday: 03:15 - 04:15 PM (1 hour after class), Room SSB 304
Tuesday: 04:45 - 05:45 PM (1 hour after class), Room SSB 304
Pre-requisite Skills: Familiarity with Logic, Programming, Analysis of Algorithms, and Probability
Grading Policy:
Quiz 1: 20%
Quiz 2: 20%
End-semester: 30%
In class tasks: 5%
Quizzes based on Assignments: 25% (5 best out of 6 HW quizzes)
Course Email: pulkitv@cse.iitm.ac.in
Please start the subject line of all course-related emails with [CS6380].

Objectives

This course surveys classical artificial intelligence with emphasis on symbolic methods: agents, search, planning, constraint satisfaction, game playing, and logical inference.

  • Historical perspective, the Turing test, physical symbol systems, and the scope of symbolic AI
  • State-space, heuristic, randomized, and optimal-path search techniques
  • Problem decomposition, rule-based systems, adversarial search, and planning
  • Propositional and first-order logic, soundness and completeness, and chaining-based inference

The goal is to equip students to model problems in AI formalisms and to understand when and why standard algorithms apply.

Course Contents

Module 1: Introduction

  • Overview and historical perspective; state of the art
  • Intelligent agents: rationality, PEAS, and agent architectures

Module 2: Solving Problems by Searching

  • Problem-solving agents and problem formulation
  • Uninformed search: breadth-first, uniform-cost, depth-first, iterative deepening
  • Informed (heuristic) search: greedy best-first and A*
  • A* properties and heuristic design

Module 3: Search in Complex Environments

  • Local search: hill climbing, simulated annealing, genetic algorithms
  • Nondeterministic actions and AND–OR search
  • Partial observability and online search

Module 4: Adversarial Search and Games

  • Minimax algorithm
  • Alpha–beta pruning
  • Evaluation functions, cutting off search, and move ordering
  • Monte Carlo Tree Search
  • Stochastic and partially observable games

Module 5: Constraint Satisfaction Problems

  • CSP formulation
  • Constraint propagation and arc consistency
  • Backtracking search for CSPs
  • Inference, backjumping, local search, and problem structure

Module 6: Logical Agents and Propositional Logic

  • Knowledge-based agents and propositional logic
  • Entailment, model checking, and validity
  • Resolution, CNF, and Horn clauses
  • Forward and backward chaining; DPLL and SAT solvers

Module 7: First-Order Logic

  • Syntax and semantics of first-order logic
  • Using first-order logic
  • Inference: unification, forward chaining, and backward chaining
  • Resolution in first-order logic

Module 8: Knowledge Representation

  • Categories and objects
  • Events, reasoning systems, and default reasoning

Module 9: Classical Planning

  • PDDL and example domains
  • Planning algorithms and heuristics
  • Advanced planning (overview)

Text Books

The primary reference is Russell and Norvig. Additional readings may be linked from the course calendar as the semester progresses.

[AIMA] Artificial Intelligence: A Modern Approach, 4th Edition. Stuart Russell and Peter Norvig. Pearson, 2020. Course resources and errata: aima.cs.berkeley.edu.

[FCAI] A First Course in Artificial Intelligence, 1st Edition. Deepak Khemani. McGraw Hill Education (India), 2013. ISBN-10: 1259029980, ISBN-13: 9781259029981. mheducation.co.in.

Course Calendar

# Date Lecture Material Readings HW
1. Mon, Jul 27 Introduction: What is AI? History and State of the Art Slides AIMA Sections 1.1–1.5 -
2. Tue, Jul 28 Intelligent Agents Slides AIMA Sections 2.1–2.3 -
3. Thu, Jul 30 Structure of Agents Slides AIMA Sections 2.3–2.4 -
4. Mon, Aug 03 Problem Formulation and Uninformed Search Slides AIMA Sections 3.1–3.4 -
— Tue, Aug 04 No class — — -
5. Thu, Aug 06 Informed Search: Greedy Best-First and A* Slides AIMA Sections 3.4–3.5 -
6. Mon, Aug 10 A* Search: Optimality and Heuristic Generation Slides AIMA Sections 3.5–3.6 HW1 out
7. Tue, Aug 11 Local Search Slides AIMA Sections 4.1 -
8. Thu, Aug 13 Local Search in Continuous Spaces and Nondeterministic Settings Slides AIMA Section 4.2–4.3 HW1 solution out
9. Mon, Aug 17 Partial Observability and Online Search Slides AIMA Sections 4.4–4.5 -
10. Tue, Aug 18 Adversarial Search and Games Slides AIMA Sections 5.1–5.3 -
11. Thu, Aug 20 Alpha-Beta Pruning Tutorial Slides AIMA Section 5.2 HW-Quiz 1; HW2 out
12. Mon, Aug 24 Alpha–Beta Pruning Tutorial (conrd.) Slides AIMA Sections 5.2 -
13. Tue, Aug 25 Evaluation Functions, Cutting Off Search, and Move Ordering Slides AIMA Section 5.2–5.3 -
14. Thu, Aug 27 Stochastic and Partially Observable Games Slides AIMA Sections 5.5–5.6 HW2 solution out
— Mon, Aug 31 Quiz 1 (Ch. 1–4 and Sections 5.1–5.3) — — —
— Tue, Sep 01 No class — — -
15. Thu, Sep 03 Constraint Satisfaction Problems Slides AIMA Section 6.1 -
16. Mon, Sep 07 Solving CSPs Slides AIMA Sections 6.2–6.3 HW3 out
17. Tue, Sep 08 Local Search for CSPs — AIMA Section 6.4 In-class test; HW-Quiz 2
18. Thu, Sep 10 Monte Carlo Tree Search — AIMA Section 5.4 -
— Mon, Sep 14 No class — Institute Holiday — — —
19. Tue, Sep 15 Advanced CSP: Inference, Backjumping, Local Search, Structure — AIMA Sections 6.3–6.5 -
20. Thu, Sep 17 CSP Problem Discussion — AIMA Chapter 6 -
21. Mon, Sep 21 Logical Agents and Propositional Logic — AIMA Sections 7.1–7.4 HW-Quiz 3; HW4 out
22. Tue, Sep 22 Entailment, Model Checking, and Validity — AIMA Sections 7.4–7.5 -
23. Thu, Sep 24 Resolution, CNF, and Horn Clauses — AIMA Section 7.5 HW4 solution out
— Mon, Sep 28 No class — — -
24. Tue, Sep 29 Propositional Agents (brief); First-Order Logic: Syntax and Semantics — AIMA Sections 7.7, 8.1–8.2 -
25. Thu, Oct 01 Forward/Backward Chaining; DPLL and SAT Solvers — AIMA Sections 7.5–7.6 HW5 out
26. Mon, Oct 05 Using First-Order Logic — AIMA Sections 8.3–8.4 HW-Quiz 4
27. Tue, Oct 06 Inference in FOL: Unification and Forward Chaining — AIMA Sections 9.1–9.3 -
28. Thu, Oct 08 Backward Chaining and Logic Programming — AIMA Section 9.4 HW5 solution out
— Mon, Oct 12 Quiz 2 (Ch. 7–9 through Section 9.4) — — —
29. Tue, Oct 13 Resolution in First-Order Logic — AIMA Section 9.5 -
30. Thu, Oct 15 Knowledge Representation: Categories and Objects (short intro) — AIMA Sections 10.1–10.2 HW-Quiz 5; HW6 out
31. Mon, Oct 19 KR: Events, Reasoning Systems, and Default Reasoning — AIMA Sections 10.3–10.6 -
— Tue, Oct 20 No class — Institute Holiday — — —
32. Thu, Oct 22 Classical Planning: PDDL and Example Domains — AIMA Section 11.1 HW6 solution out
33. Mon, Oct 26 Classical Planning: Algorithms and Heuristics — AIMA Sections 11.2–11.3 -
34. Tue, Oct 27 Course Summary and Review — AIMA Chapters 1–11 -
35. Thu, Oct 29 Advanced Planning: A Whirlwind Tour — AIMA Sections 11.4–11.6 HW-Quiz 6
— Wed, Nov 11 End-Semester Exam (Ch. 1–11) — — —