MTech Artificial Intelligence And Robotics syllabus for 2 Sem 2020 scheme 20MAE243

Introduction & Propositional Logic:

History of AI, Propositional logic-Computability & Complexity, Applications, Ist Order Predicate logic, limitations of logic.

Logic Programming:

Prolog system & Implementation, Execution control, Constraint Logic programming, Planning and examples.

Machine Learning and Data Mining:

Data analysis, learning rule, nearest neighbor method, Decision tree learning, Clustering-Distance matrices, Hierarchical learning.

Neural Networks:

Mathematical Model, Neural anociative memory, spelling correction program, support vector machine, application of deep learning, application of neural network.

Robotics:

Introduction, Mathematical representation of robots, kinematics of serial manipulators, kinematics of parallel manipulators, Dynamics of manipulators.

Course outcomes:

At the end of the course the student will be able to:

1. Apply the propositional logic in Artificial Intelligence.

2. Perform Data Mining.

3. Model Neural Network and Robotic Kinematics

Question paper pattern:

The SEE question paper will be set for 100 marks and the marks scored will be proportionately reduced to 60.

• The question paper will have ten full questions carrying equal marks.
• Each full question is for 20 marks.
• There will be two full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub question covering all the topics under a module.
• The students will have to answer five full questions, selecting one full question from each module.

Textbook/ Textbooks

1 Introduction to Artificial Intelligence Wolfgang Ertel Springer 2017

2 Robotics-Fundamental Concepts and Analysis Ashitara Ghosal Oxford Press 2006

Reference Books

1 Artificial Intelligence and Machine Learning Vinod Chandra S.S., and Anand Hareendran S PHI Learning Pvt. Ltd 2014

2 Introduction to Robotics-Analysis, Control, Application Saeed B Niku Wiley 2011