Course Name: Artificial Intelligence : 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 – 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.


Course Instructor

Media Object

Prof. Deepak Khemani

Department of Computer Science and Engineering, IIT Madras Chennai 600036, India
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Teaching Assistant(s)

KEVIN ALEX MATHEWS

 Course Duration : Jul-Oct 2016

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 Syllabus

 Enrollment : 23-May-2016 to 18-Jul-2016

 Exam registration : 25-Jul-2016 to 20-Sep-2016

 Exam Date : 16-Oct-2016, 23-Oct-2016

Enrolled

5284

Registered

82

Certificate Eligible

38

Certified Category Count

Gold

2

Elite

16

Successfully completed

20

Participation

20

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.
  • Exam score has been moderated by faculty
  • NOTE:Assignment 1A-& 1B marks has been taken an average and displayed under Week 1
Artificial Intelligence : Search Methods For Problem solving - Toppers list

KARTHIKEYAN NAGARAJAN 92%

MERCEDES BENZ RD INDIA

SATYA HARI PRASAD YALLA 90%

FLIPKART

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.