ARTIFICIAL INTELLIGENCE

Paper Code: 
24DCAI701A
Credits: 
03
Periods/week: 
03
Max. Marks: 
100.00
Objective: 

Course Objectives:

The course will enable the students to

  1. Explore the concepts of artificial intelligence, expert systems and their applications.

            2. Apply problem solving techniques in AI.

 

Course Outcomes: 

Course

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

Course Code

Course

Title

 

24DCAI 701A

 

ARTIFICIAL INTELLIGENCE

(Theory)

CO91. Formulate foundational concepts and techniques of Artificial Intelligence using state space tree

CO92. Identify suitable search techniques to solve the complex problem

CO93. Elaborate knowledge representation schemes in AI

CO94. Identify diverse slot-and-filler structures in AI frameworks.

CO95. Design a simple recommender system.

CO96. Contribute     effectively in course-specific interaction

 

Approach in teaching:

Interactive Lectures, Discussion, PowerPoint Presentations, Informative videos

 

Learning activities for the students: 

Self-learning assignments, Effective questions, presentations.

 

 

 

Assessment tasks will include Class Test on the topics, Semester end examinations, Quiz, Student presentations and assignments.

 

9.00
Unit I: 
Overview of Artificial Intelligence:

Introduction, Importance of AI, AI and Related Field. Knowledge: General Concepts: Introduction, Definition and Importance of Knowledge. Introduction to Knowledge-Based Systems. The AI Problems, AI Techniques, Defining the Problem as a State Space Search (water jug problem), Production systems.

 

9.00
Unit II: 
Search Techniques:

Search space control strategy, Breadth First Search and Depth First Search. Heuristic Search Techniques: Generate-and-Test, Hill Climbing: Simple and Steepest-Ascent Hill Climbing, Best-First Search: OR Graphs, The A* Algorithm, Problem Reduction: AND-OR Graphs, The AO* Algorithm.

 

9.00
Unit III: 
Representations and Mappings:

Formalized Symbolic Logics: Introduction, Syntax and Semantics for Propositional Logic, Syntax and Semantics for FOPL, Properties of Wffs, Conversion of Clausal Form, Inference Rules, Unification, Resolution by refutation, Non-deductive Inference Methods and Representations Using Rules

 

9.00
Unit IV: 
Weak Slot-and-Filler Structures:

Semantic nets, Frames, Frames as Sets and Instances.

Strong Slot-and-Filler Structures: Conceptual Dependency, Scripts.

 

9.00
Unit V: 
Expert Systems:

introduction, features, need, applications & importance. Representing and using domain knowledge, expert systems shells, and knowledge acquisition. Recommendation System and types of recommendation system, Content-based recommender systems, collaborative filtering (CF). Advantages and drawbacks. Applications of recommendation systems.

ESSENTIAL READINGS: 

Suggested Text Books:

  1. E. Rich and K. Knight, “Artificial Intelligence”, Tata Mc Graw Hill, 2010.
  2. D.W. Patterson, “Introduction to AI and Expert Systems”, PHI, 1999.
  3. C.C. Aggarwal, Recommender Systems: The Textbook, Springer, 2016
  4. I.Gupta and G. Nagpal. Artificial Intelligence and Expert    Systems. (n.p.): Mercury Learning and   Information,2020.
REFERENCES: 

Suggested Reference Books:

  1. N.J. Nilsson, “Principles of AI”, Narosa Publ. House, 2014.
  2. Peter Jackson, “Introduction to Expert Systems”, AWP, M.A., 1992.
  3. M. Sasikumar, S. Ramani, “Rule Based Expert Systems”, Narosa Publishing            House, 1994

 

Reference Journals:

  1. The International Journal of Research on Intelligent Systems for Real Life Complex Problems  springer :https://www.springer.com/journal/10489?gclid=CjwKCAjw9pGjBhB-EiwAa5jl3N46-_KoR8ZWrpEUOyY6I4BC2cGi1IOSFFDUTGj6V3pumtW56Lj8OxoC7O4QAvD_BwE
  2. Journal of Artificial Intelligence Research (JAIR) : https://www.jair.org/index.php/jair

 

e-Resources including links

  1. Course of Artificial Intelligence by IITM    NPTEL:https://nptel.ac.in/courses/106105077
  2. Elements of AI course by The University of Helsinki :        https://www.elementsofai.com/

 

Academic Year: 
2024-25
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