Artificial Intelligence: Knowledge Representation And Reasoning

By Prof. Deepak Khemani | IIT Madras

Learners enrolled: 17089

An intelligent agent needs to be able to solve problems in its world. The ability to create representations of the domain of interest and reason with these representations is a key to intelligence. In this course we explore a variety of representation formalisms and the associated algorithms for reasoning. We start with a simple language of propositions, and move on to first order logic, and then to representations for reasoning about action, change, situations, and about other agents in incomplete information situations. This course is a companion to the course “Artificial Intelligence: Search Methods for Problem Solving” that was offered recently and the lectures for which are available online.

INTENDED AUDIENCE : BE/ME/MS/MSc/PhD students

PREREQUISITES : Some exposure to formal languages, logic and programming

INDUSTRY SUPPORT : Software companies dealing with knowledge and reasoning, including the semantic web and semantic search.

Summary

Course Status :	Completed
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Computer Science and Engineering Artificial Intelligence Data Science
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	24 Jan 2022
End Date :	15 Apr 2022
Enrollment Ends :	07 Feb 2022
Exam Date :	23 Apr 2022 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction. History and Philosophy.

Week 2: Symbolic Reasoning. Truth, Logic, and Provability.

Week 3: Propositional Logic. Direct Proofs. The Tableau Method.

Week 4: First Order Logic. Universal Instantiation. The Unification Algorithm.

Week 5: Forward and Backward Chaining. The Resolution Refutation Method.

Week 6: Horn Clauses and Logic Programming. Prolog.

Week 7: Rule Based Systems. The OPS5 Language. The Rete Algorithm.

Week 8: Representation in First Order Logic. Conceptual Dependency.

Week 9: Frames. Description Logics and the Web Ontology Language

Week 10: Taxonomies and Inheritance. Default Reasoning.

Week 11: Circumscription. Auto-epistemic Reasoning. Event Calculus

Week 12: Epistemic Logic. Knowledge and Belief.

Books and references

Text Books

1. Ronald J. Brachman, Hector J. Levesque: Knowledge Representation and Reasoning, Morgan Kaufmann, 2004.

2. Deepak Khemani. A First Course in Artificial Intelligence, McGraw Hill Education (India), 2013.

Reference Books

1. Schank, Roger C., Robert P. Abelson: Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures. Hillsdale, NJ: Lawrence Erlbaum, 1977.

2. R. C. Schank and C. K. Riesbeck: Inside Computer Understanding: Five Programs Plus Miniatures, Lawrence Erlbaum, 1981.

3. Murray Shanahan: A Circumscriptive Calculus of Events. Artif. Intell. 77(2), pp. 249-284, 1995.

4. Grigoris Antoniou and Frank van Harmelen, A Semantic Web Primer, 2nd Ed, MIT Press, 2008.

5. John F. Sowa: Conceptual Structures: Information Processing in Mind and Machine, Addison–Wesley Publishing Company, Reading Massachusetts, 1984.

6. John F. Sowa: Knowledge Representation: Logical, Philosophical, and Computational Foundations, Brooks/Cole, Thomson Learning, 2000.

Instructor bio

Prof. Deepak Khemani

IIT Madras

Deepak Khemani is Professor at Department of Computer Science and Engineering, IIT Madras. He completed his B.Tech. (1980) in Mechanical Engineering, and M.Tech. (1983) and PhD. (1989) in Computer Science from IIT Bombay, and has been with IIT Madras since then. In between he spent a year at Tata Research Development and Design Centre, Pune and another at the youngest IIT at Mandi. He has had shorter stays at several Computing departments in Europe. Prof Khemani’s long-term goals are to build articulate problem solving systems using AI that can interact with human beings. His research interests include Memory Based Reasoning, Knowledge Representation and Reasoning, Planning and Constraint Satisfaction, Qualitative Reasoning and Natural Language Processing.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 23 April 2022 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

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