Syllabus - Artificial Intelligence (IT-504 (A))

Information Technology

Artificial Intelligence (IT-504 (A))

V-Semester

Unit I

Meaning and definition of artificial intelligence, Production systems, Characteristics of production systems, Study and comparison of breadth first search and depth first search techniques, other Search Techniques like hill Climbing, Best first Search. A* algorithm, AO* algorithms etc, and various types of control strategies.

Unit II

Knowledge Representation, Problems in representing knowledge, knowledge representation using propositional and predicate logic, comparison of propositional and predicate logic, Resolution, refutation, deduction, theorem proving, inferencing, monotonic and non-monotonic reasoning.

Unit III

Probabilistic reasoning, Baye's theorem, semantic networks, scripts, schemas, frames, conceptual dependency, fuzzy logic, forward and backward reasoning.

Unit IV

Game playing techniques like minimax procedure, alpha-beta cut-offs etc, planning, Study of the block world problem in robotics, Introduction to understanding, natural language processing.

Unit V

Introduction to learning, Various techniques used in learning, Introduction to neural networks, applications of neural networks, common sense, reasoning, some example of expert systems.

Course Objective

To present an overview of artificial intelligence (AI) principles and approaches. Develop a basic understanding of the building blocks of AI.

Course Outcome

["Explain what constitutes 'Artificial' Intelligence and how to identify systems with Artificial Intelligence.", "Know how to build simple knowledge-based systems.", "Have the ability to apply knowledge representation, reasoning, and machine learning techniques to real-world problems."]

Practicals

Reference Books

  • Rich E and Knight K, 'Artificial Intelligence', TMH, New Delhi.

  • Nelsson N.J., 'Principles of Artificial Intelligence', Springer Verlag, Berlin.