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AI Syllabus PDF

This document outlines an Artificial Intelligence course syllabus. It includes 4 units that will be covered: Introduction to AI concepts like problem solving and search strategies; Knowledge representation using logic and languages like Prolog; Reasoning under uncertainty using probability, Bayes rule, and fuzzy logic; Planning and learning techniques like conditional planning, multi-agent planning, reinforcement learning, and neural networks. The course aims to introduce basic AI principles and explore areas of application. Students will understand concepts like intelligent agents, knowledge representation, natural language processing, and more.

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344 views1 page

AI Syllabus PDF

This document outlines an Artificial Intelligence course syllabus. It includes 4 units that will be covered: Introduction to AI concepts like problem solving and search strategies; Knowledge representation using logic and languages like Prolog; Reasoning under uncertainty using probability, Bayes rule, and fuzzy logic; Planning and learning techniques like conditional planning, multi-agent planning, reinforcement learning, and neural networks. The course aims to introduce basic AI principles and explore areas of application. Students will understand concepts like intelligent agents, knowledge representation, natural language processing, and more.

Uploaded by

Vishal Sharma
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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MRSPTU B.TECH.

COMPUTER SCIENCE & ENGINEERING SYLLABUS 2016


BATCH ONWARDS UPDATED ON 12.9.2018

ARTIFICIAL INTELLIGENCE
Subject Code: BCSE1-766 LTPC Duration: 45 Hrs.
3104

Course Objectives:
This course will introduce the basic principles in artificial intelligence research. It will cover
simple representation schemes, problem solving paradigms, constraint propagation, and
search strategies. Areas of application such as knowledge representation, natural language
processing, expert systems, vision and robotics will be explored
Course Outcomes:
CO1: Understand the concept of Artificial intelligence, problem solving and various types of
search strategies.
CO2: Understand the concept of Knowledge base, knowledge representation, AI languages &
tools and various planning techniques.
CO3: Identify uncertainty and understand fuzzy logic concept to handle uncertainty.
CO4: Understand the COURSE of AI agents and various COURSE methods it also includes
neural network and includes the communication of AI agents and natural language
processing.
UNIT-I (11 Hrs.)
Introduction: History of AI - Intelligent agents – AI and Applications - Problem spaces and
search - Heuristic Search techniques – Best-first search – Informal search strategies-A*
algorithm, Iterative deepening A*(IDA), small memory A*(SMA). Game Playing: Minimax
search procedure - Adding alpha-beta cutoffs
UNIT-II (12 Hrs.)
Knowledge Representation: Approaches and issues in knowledge representation Knowledge -
Based Agent- Propositional Logic – Predicate logic –Reasoning, AI languages Prolog, Lisp.
UNIT-III (11 Hrs.)
Reasoning under uncertainty: Implementation- Basic probability notation - Bayes rule –
Certainty factors and rule based systems - Bayesian networks, Fuzzy Logic.
UNIT IV (11 Hrs.)
Planning and COURSE: Basic representation of plans - conditional planning - Multi-Agent
planning. Forms of COURSE - inductive COURSE - Reinforcement COURSE - COURSE
decision trees - Neural Networks. Communication: Natural language processing, Formal
Grammar, Parsing

Recommended Books:
1. Elaine Rich, Kevin Knight and Shivashankar B.Nair, ‘Artificial Intelligence’, 3rd Edn.,
Tata McGraw-Hill, 2009.
2. Stuart J. Russell and Peter Norvig, ‘Artificial Intelligence: A Modern Approach’, Pearson
Education Asia, 2nd Edn., 2003.
3. N.P. Padhy, ‘Artificial Intelligence and Intelligent System’, Oxford University Press, 2nd
Edn., 2005.
4. Rajendra Akerkar, ‘Introduction to Artificial Intelligence’, Prentice-Hall of India, 2005.
5. Patrick Henry Winston, ‘Artificial Intelligence’, Pearson Education Inc., 3rd Edn., 2001.
6. Eugene Charniak and Drew Mc Dermott, ‘Introduction to Artificial Intelligence’, Addison-
Wesley, ISE Reprint, 1998.
7. Nils J. Nilsson, ‘Artificial Intelligence - A New Synthesis’, Harcourt Asia Pvt. Ltd.,
Morgan Kaufmann, 1988.

MAHARAJA RANJIT SINGH PUNJAB TECHNICAL UNIVERSITY, BATHINDA

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