Course Name: AI: search methods for problem Solving

Course abstract

For an autonomous agent to behave in an intelligent manner it must be able to solve problems. This means it should be able to arrive at decisions that transform a given situation into a desired or goal situation. The agent should be able to imagine the consequence of its decisions to be able to identify the ones that work. In this first course on AI we study a wide variety of search methods that agents can employ for problem solving.

In a follow up course – AI: Knowledge Representation and Reasoning – we will go into the details of how an agent can represent its world and reason with what it knows. These two courses should lay a strong foundation for artificial intelligence, which the student can build upon. A third short course – AI: Constraint Satisfaction Problems – presents a slightly different formalism for problem solving, one in which the search and reasoning processes mentioned above can operate together.


Course Instructor

Media Object

Prof. Deepak Khemani

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 then 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.


More info

Teaching Assistant(s)

SHIKHA SINGH

Ph.D., Computer Science, IIT Madras

G.Devi

PhD Scholar, CSE, IITM

 Course Duration : Jul-Oct 2017

  View Course

 Enrollment : 17-May-2017 to 24-Jul-2017

 Exam registration : 30-Aug-2017 to 20-Sep-2017

 Exam Date : 22-Oct-2017

Enrolled

8245

Registered

190

Certificate Eligible

76

Certified Category Count

Gold

0

Silver

0

Elite

26

Successfully completed

50

Participation

77

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score.
AI: search methods for problem Solving - Toppers list

VAMSHI GANGADHAR CHILUKA 80%

INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, DESIGN AND MANUFACTURING, KANCHEEPURAM

TAMAL SARKAR 74%

PONDICHERRY UNIVERSITY

VARUN PANTHRI 73%

University School of Information and Communication Technology

SUSHMITA KUMARI 72%

THAKUR POLYTECHNIC

ASHISH KUMAR 71%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

Enrollment Statistics

Total Enrollment: 8245

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Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.