Schedule

Instructors		Prof. Pallab Dasgupta Prof. Partha Pratim Chakrabarti
Timing		WED (10:00 AM – 10:55 AM), THU (9:00 AM –9:55 AM), FRI (11:00 AM –11:55 PM)
Venue		Room No: NR-421, Nalanda Academic Complex
Team Code		732ru1m
Teaching Assistants		1. Briti Gangopadhyay (briti_gangopadhyay@iitkgp.ac.in), 2. Sumanta Dey (sumanta.dey@iitkgp.ac.in), 3. Ajinkya Waghmare (waghmareaju1216@gmail.com), 4. Somesh Kishor Kharat (somesh3199@kgpian.iitkgp.ac.in), 5. Debjyoti Das Adhikari (debjyoti.das.adhikary@gmail.com) 6. Aayush Prasad (aayuprasad@iitkgp.ac.in) 7. Maj Rakshit Sharma 8. Naincy Vimal (naincyvimal2109@kgpian.iitkgp.ac.in)

Announcements

1. Marks distribution: Class Test: 10% Mid Sem: 30% Project: 15% End Sem: 40% Attendance: 5%

2. Class Test 1 on 2nd September at 11:00 AM - 12:55 PM

Syllabus

Introduction	Course Introduction, Motivation.	[1 hour]
Problem solving by search	State Space, Problem Reduction, Game Playing, Constraint Satisfaction.	[7 hours]
Automated Reasoning	Proposition and first order logic, inference and deduction, resolution refutation, answer extraction, knowledge based systems, logic programming and constrained logic programming, non-monotonic reasoning.	[6 hours]
Planning	State-space, plan space and partial order planning, planning algorithms.	[4 hours]
Reasoning under uncertainty	Probabilistic reasoning, belief networks	[5 hours]
Learning	Inductive learning, decision trees, logical approaches, computational learning theory, neural networks, reinforcement learning, Intelligent agents, natural language understanding, Applications.	[8 hours]

Books and References

[1]	Stuart Russell, Peter Norvig, Artificial intelligence : A Modern Approach, Prentice Hall, Fourth edition, 2020.
[2]	Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan-Kaufmann, 1998.
[3]	Judea Pearl, Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addison-Wesley Publishing Company, 1984.
[4]	Biere, A., Heule, M., Van Maaren, H., Walsh, T., Handbook of Satisfiability, IOS Press, 2009.

Classes Material

Week	Topic	Chapter	PDF	Annotated PDF	Video Link	Tutorial
Week 1	Introduction	Introduction	Link	-	Link	-
	Automated Problem Solving	Automated Problem Solving	Link	Link	Link	-
		State Space Search	Link	Link	Link	-
Week 2		Heuristic Search	Link	Link	Link	-
		Heuristic Search
		Game Trees	Link	Link	Link	-
Week 3		Game Trees
		Holiday 1	-	-	-	-
		Holiday 2	-	-	-	-
Week 4		Local Search	Link	-	Link	-
	Propositional Logic	Propositional Logic	Link	Link	Link	-
		Propositional Logic to Predicate Logic	Link	Link	Link	-
Week 5		Predicate Logic Fundamentals	Link	Link	Link	-
		Resolution Refutation	Link	Link	Link	-
		Class Test 1	-	-	-	-
Week 6	Propositional Logic	Resolution Refutation	Link	Link	Link	-
		Constraint Satisfaction Problems	Link	Link	Link	-
	Planning in AI	Planning in AI Part 1	Link	Link	Link	-
Week 7		Planning in AI Part 2	Link	Link	Link	-
		Planning in AI Part 3	Link	Link	Link	-
		Tutorials	-	-	-	Questions Solutions
Week 8	Reasoning Under Uncertainty	Part 1	Link	Link	Link	-
		Part 2	Link		Link	-
		Tutorial (CSP, Bayes Net, Graph Plan)	Link		-	Answers
Week 9	Machine Learning	Machine Learning Fundamentals	Link	-	Link	-
		Learning Decision Trees	Link	-	Link	-
Week 10		Neural Networks	Link	-	Link	-
		Deep Learning Fundamentals	Link	-	Link	-
Week 10		Reinforcement Learning Fundamentals	Link	-	Link	-

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