AI:Constraint Satisfaction

By Prof. Deepak Khemani | IIT Madras

Learners enrolled: 4112

Human beings solve problems in many different ways. Problem solving in artificial intelligence (AI) is inspired from these diverse approaches. AI problem solvers may be based on search, on memory, or on knowledge representation and reasoning. An approach to problem solving is to pose problems as constraint satisfaction problems (CSP), and employ general methods to solve them. The task of a user then is only to pose a problem as a CSP, and then call an off-the-shelf solver. CSPs are amenable to combining search based methods with reasoning. In this 2 credit course we will look at general approaches to solving finite domain CSPs, and explore how search can be combined with constraint propagation to find solutions.

This course is a companion to the course “Artificial Intelligence: Search Methods for Problem Solving” that was offered recently and “Artificial Intelligence: Knowledge Representation & Reasoning” that is being offered concurrently. The lectures for both courses are available online.

INTENDED AUDIENCE : Both UG and PG students studying Computer Science (any degree) can take it.

PRE-REQUISITES : Exposure to AI: Search Methods for Problem Solving and AI: Knowledge Representation & Reasoning helps, but is not necessary.

INDUSTRY SUPPORT : Software companies dealing with artificial intelligence applications

Summary

Course Status :	Upcoming
Course Type :	Elective
Duration :	8 weeks
Start Date :	24 Jan 2022
End Date :	18 Mar 2022
Exam Date :	27 Mar 2022 IST
Category :	Computer Science and Engineering Artificial Intelligence
Credit Points :	2
Level :	Undergraduate/Postgraduate

Course layout

Module 1: Constraint satisfaction problems (CSP), examples.

Module 2: Constraint networks, equivalent and projection networks.

Module 3: Constraint propagation, arc consistency, path consistency, i-consistency.

Module 4: Directional consistency and graph ordering, backtrack free search, adaptive consistency.

Module 5: Search methods for solving CSPs, lookahead methods, dynamic variable and value ordering.

Module 6: Lookback methods, Gaschnig's backjumping, graph based backjumping, conflict directed back jumping. Combing lookahead with lookback, learning.

Module 7: Model based systems, model based diagnosis, truth maintenance systems, planning as CSP. Wrapping up.

Books and references

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

2. Rina Dechter, Constraint Processing, Morgan Kaufmann, 2003.

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: 27 March 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 6 assignments out of the total 8 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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