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Intro

NPTEL: Artificial Intelligence: Knowledge Representation and Reasoning

 with  Deepak Khemani
Sponsored
Complexity Tutorials
Santa Fe University via Complexity Explorer

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. 

Syllabus

Week 1 Introduction, Propositional Logic, Proof Systems

Week 2 Tableau Method, Resolution Method, First Order Logic (FOL) 

Week 3 FOL Semantics, Unification, Forward Chaining with the Rete Algorithm 

Week 4 Rete example, Reification, Event Calculus, Conceptual Dependency (CD) Theory 

Week 5 Conceptual Dependency Theory, Mapping from Natural Language, Goal Trees 

Week 6 Logic Programming with Prolog, Resolution Refutation in FOL 

Week 7 SLD Resolution, Frames, Scripts 

Week 8 Goals and Plans, Description Logic (DL), Structure Matching 

Week 9 Classification in DL, A-Box Reasoning, Extensions of DL, ALC 

Week 10 Inheritance Networks, Default Reasoning, Circumscription 

Week 11 Event Calculus, Default Extensions, Epistemic Reasoning 

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Cost Free Online Course
Pace Upcoming
Provider NPTEL
Language English
Hours 3-4 hours a week
Calendar 12 weeks long

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