CS60045 Artificial Intelligence

CS60045 Artificial Intelligence

Autumn 2021, L-T-P: 3-0-0

Schedule

Instructors     Prof. Pallab Dasgupta
Prof. Partha Pratim Chakrabarti
Timing     WED (10:00–10:55 AM), THU (9:00–9:55 AM), FRI (11:00–11:55 AM)
Venue     MS Teams (Team code: nz9boz9)
Teaching Assistants     Briti Gangopadhyay (briti_gangopadhyay@iitkgp.ac.in),
Sumanta Dey (sumanta.dey@iitkgp.ac.in),
Somnath Hazra (sommnathsh@gmail.com),
Ritikesh Gupta (ritikeshkgp@iitkgp.ac.in)
Kshitiz Sharma (kshitizs2809@iitkgp.ac.in)
Bagde Ankit (ankit2000.bagde@iitkgp.ac.in)

Announcements

1. Tutorial on 28^th August at 10:00 AM

2. Class Test 1 on 4^th September at 10:00 AM

3. Please mail Sumanta Dey if you did not receive any mail from him regarding Moodle account.

4. Tutorial on 11^th September at 9:00 AM

5. Class Test 1 (re-test) on 17^th September at 6:30 PM

6. Class Test 2 on 25^th September at 9:30 AM

7. Class Test 3 on 8^th October

8. Class Test 4 on 5^th November at 6:00 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.

Online Material

    Week         Topic         Chapter         PDF         PDF(Annotated)         YouTube Video         Tutorial         Attendance

Week 1 Introduction Introduction Introduction Link 11^th August

Automated Problem Solving Automated Problem Solving Automated Problem Solving Automated Problem Solving Link 12^th August

State Space Search State Space Search State Space Search Link 13^th August

Week 2 Heuristic Search Heuristic Search Heuristic Search Link 18^th August

19^th August

Week 3 Game Trees Game Trees Game Trees Link 28^th August Tutorial 25^th August

26^th August

Local Search Local Search Link 27^th August

Week 4 Logic and Deduction Propositional logic Propositional Logic Propositional Logic Link 1^st September

Propositional Logic to Predicate Logic Propositional Logic to Predicate Logic Propositional Logic to Predicate Logic Link 2^nd September

Predicate Logic Fundamentals Predicate Logic Fundamentals Predicate Logic Fundamentals Link 3^rd September

Week 5 Resolution Refutation Inference Using Resolution Refutation Inference Using Resolution Refutation Link 11^th September Tutorial 8^th September

9^th September

Constraint Satisfaction Problems Constraint Satisfaction Problems Constraint Satisfaction Problems Link 10^th September

Week 6 Planning in AI Planning in AI Part 1 Planning in AI Part 1 Planning in AI (Combined) Link 15^th September

Planning in AI Part 2 Planning in AI Part 2 Link 16^th September

Planning in AI Part 3 Planning in AI Part 3 Link 17^th September Tutorial
Solutions 17^th September

Week 7 Reasoning Under Uncertainty Reasoning Under Uncertainty Part 1 Reasoning under Uncertainty Part 1 Reasoning under Uncertainty (Combined) Link 22^nd September

Reasoning Under Uncertainty Part 2 Reasoning Under Uncertainty Part 2 Link 23^rd September

Reasoning Under Uncertainty Part 3 Link 29^th September Tutorial
Solutions 24^th September

Week 8 Learning Machine Learning Fundamentals Machine Learning Fundamentals Link 30^th September

1^st October

Week 9 Learning Decision Trees Learning Decision Trees Link 6^th October

7^th October

Week 10 Neural Networks Neural Networks and Deep Learning Link 20^th October

Deep Learning Fundamentals Neural Networks and Deep Learning Link 21^st October

Reinforcement Learning Fundamentals Reinforcement Learning Link 29^th October Tutorial
Solutions 22^nd October

Week 12 Building Trusted AI Building Trusted AI

Previous course pages: 2020 | 2019 | 2018

Week	Topic	Chapter	PDF	PDF(Annotated)	YouTube Video	Tutorial	Attendance
Week 1	Introduction	Introduction	Introduction		Link		11^th August
Automated Problem Solving	Automated Problem Solving	Automated Problem Solving	Automated Problem Solving	Link		12^th August
State Space Search	State Space Search	State Space Search	Link		13^th August
Week 2	Heuristic Search	Heuristic Search	Heuristic Search	Link		18^th August
19^th August
Week 3	Game Trees	Game Trees	Game Trees	Link	28^th August Tutorial	25^th August
26^th August
Local Search	Local Search		Link		27^th August
Week 4	Logic and Deduction	Propositional logic	Propositional Logic	Propositional Logic	Link		1^st September
Propositional Logic to Predicate Logic	Propositional Logic to Predicate Logic	Propositional Logic to Predicate Logic	Link		2^nd September
Predicate Logic Fundamentals	Predicate Logic Fundamentals	Predicate Logic Fundamentals	Link		3^rd September
Week 5	Resolution Refutation	Inference Using Resolution Refutation	Inference Using Resolution Refutation	Link	11^th September Tutorial	8^th September
9^th September
Constraint Satisfaction Problems	Constraint Satisfaction Problems	Constraint Satisfaction Problems	Link		10^th September
Week 6	Planning in AI	Planning in AI Part 1	Planning in AI Part 1	Planning in AI (Combined)	Link		15^th September
Planning in AI Part 2	Planning in AI Part 2	Link		16^th September
Planning in AI Part 3	Planning in AI Part 3	Link	17^th September Tutorial Solutions	17^th September
Week 7	Reasoning Under Uncertainty	Reasoning Under Uncertainty Part 1	Reasoning under Uncertainty Part 1	Reasoning under Uncertainty (Combined)	Link		22^nd September
Reasoning Under Uncertainty Part 2	Reasoning Under Uncertainty Part 2	Link		23^rd September
Reasoning Under Uncertainty Part 3		Link	29^th September Tutorial Solutions	24^th September
Week 8	Learning	Machine Learning Fundamentals	Machine Learning Fundamentals		Link		30^th September
1^st October
Week 9	Learning Decision Trees	Learning Decision Trees		Link		6^th October
7^th October
Week 10	Neural Networks	Neural Networks and Deep Learning		Link		20^th October
Deep Learning Fundamentals	Neural Networks and Deep Learning		Link		21^st October
Reinforcement Learning Fundamentals	Reinforcement Learning		Link	29^th October Tutorial Solutions	22^nd October
Week 12	Building Trusted AI	Building Trusted AI

CS60045 Artificial Intelligence

Autumn 2021, L-T-P: 3-0-0

Instructors		Prof. Pallab Dasgupta Prof. Partha Pratim Chakrabarti
Timing		WED (10:00–10:55 AM), THU (9:00–9:55 AM), FRI (11:00–11:55 AM)
Venue		MS Teams (Team code: nz9boz9)
Teaching Assistants		Briti Gangopadhyay (briti_gangopadhyay@iitkgp.ac.in), Sumanta Dey (sumanta.dey@iitkgp.ac.in), Somnath Hazra (sommnathsh@gmail.com), Ritikesh Gupta (ritikeshkgp@iitkgp.ac.in) Kshitiz Sharma (kshitizs2809@iitkgp.ac.in) Bagde Ankit (ankit2000.bagde@iitkgp.ac.in)

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]

[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.