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Courses » Artificial Intelligence: Knowledge Representation And Reasoning

Artificial Intelligence: Knowledge Representation And Reasoning

ABOUT THE COURSE:
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

PRE-REQUISITES: Some exposure to formal languages, logic and programming

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

13167 students have enrolled already!!

COURSE INSTRUCTOR:
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 LAYOUT
Week 1: Introduction, Propositional Logic, Syntax and Semantics
Week 2: Proof Systems, Natural Deduction, Tableau Method, Resolution Method
Week 3: First Order Logic (FOL), Syntax and Semantics, Unification, Forward Chaining
Week 4: The Rete Algorithm, Rete example, Programming Rule Based Systems
Week 5: Representation in FOL, Categories and Properties, Reification, Event Calculus
Week 6: Conceptual Dependency (CD) Theory, Understanding Natural Language
Week 7: Deductive Retrieval, Backward Chaining, Logic Programming with Prolog
Week 8: Resolution Refutation in FOL, FOL with Equality, Complexity of Theorem Proving
Week 9: Semantic Nets, Frames, Scripts, Goals and Plans
Week 10: Description Logic (DL), Structure Matching, Classification
Week 11: Extensions of DL, The ALC Language, Inheritance in Taxonomies
Week 12: Default Reasoning, Circumscription, The Event Calculus Revisited
Week 13: Default Logic, Autoepistemic Logic, Epistemic Logic, Multi Agent Scenarios

CERTIFICATION EXAM:

1.The exam is optional for a fee.
2.Date and Time of Exams: April 28 (Saturday) and April 29 (Sunday) : Morning session 9am to 12 noon; 
3.Exam for this course will be available in one session on both 28 and 29 April. 
4.Registration url: Announcements will be made when the registration form is open for registrations.
5.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.


CERTIFICATE:

1. Final score will be calculated as : 25% assignment score + 75% final exam score
2. 25% assignment score is calculated as 25% of average of Best 8 out of 12 assignments.
3.E-Certificate will be given to those who register and write the exam and score greater than or equal to 40% final score. Certificate will have your name, photograph and the score in the final exam with the breakup. It will have the logos of NPTEL and Indian Institute of Technology,Madras. It will be e-verifiable at nptel.ac.in/noc.