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2026: Advanced Artificial Intelligence

CS5201/CS5205: Advanced Artificial Intelligence & Lab (Spring 2026)

This course will provide a basic understanding of classical artificial intelligence that includes different search methods, constraint satisfaction problems, logic, planning methods, etc. We may explore some data driven methods if time permits.

Lecture schedule

Monday — 1400-1500 (LT001);    Tuesday — 1600-1700 (LT001);    Thursday — 1600-1700 (LT001);

Lab schedule

Friday — 0900-1200;
Venue — CSE Lab, Block-2;


Instructor & TAs

Instructor TAs
  • Sophia Jamil
  • Ashish Rao
  • Aditya Singh
  • Jenil Radadiya
  • Anirudh Kandwal
  • Ravi Kumar Paswan
  • Sanjib Chowdhury
  • Shalini Singh
  • Kijen Longren
  • Vikram Kumar
  • Nishant Kumar

Syllabus

Introduction and motivation Artificial Intelligence, intelligent agents, nature of environments
Problem-solving by searching: Example problems, uninformed, informed search strategies
Uninformed/ blind search techniques: Breadth-first search (BFS), Depth-first search (DFS), Uniform-cost search (UCS)
Informed search: Heuristic function design and evaluation, A* search
Beyond classical search: local search techniques and optimization, hill climbing, simulated annealing, beam search
Adversarial search: Games, optimal decision in games, min-max, alpha-beta pruning, partially observable games
Problem reduction techniques: And-OR (AO) and AO*
Constraint Satisfaction Problem (CSP): definition and examples of CSPs, basic techniques: backtracking search, forward checking, arc consistency
Knowledge Representation, Reasoning, and Planning: Propositional logic, first-order logic, inference, planning
Learning Techniques: meta-heuristic (genetic algorithm), Bayesian, decision tree, etc.
Some advanced techniques of AI and its applications


Books

  • Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Pearson, 2022.
  • Nils J Nilsson, Artificial Intelligence: A New Synthesis, Morgan Kaufmann


Lecture Slides

Topic Slides
Introduction pdf
Automated problem solving pdf
State space search pdf
Heuristic search pdf
Game tree search pdf
CSP pdf
Propositional logic pdf
SAT pdf
Predicate logic
Prolog programming
Local search
Introduction to Planning
Probabilistic reasoning
Decision trees


Lab schedule

Topic Slides Assignment Deadline
Warmup NA NA NA
State space-1 NA pdf,
Submission procedure,
Submit here
26.01.2026
State space-2 NA pdf,
All testcases,
Upload 'assg02.cpp' or 'assg02.py'
and 'README02.txt'
02.02.2026
State space-3 NA pdf
Upload 'assg03.cpp' or 'assg03.py'
and 'README03.txt'
15.02.2026
CSP NA pdf,
20.02.2025
SAT NA pdf
10.03.2025


Projects


Last modified: 2026/02/20 07:06:51.