BEEZ072

Artificial Intelligence

L-T-P3-0-0 Credits3 Session2025-26 TypeTheory
Appears in 1 semester

B.Tech Electrical & Computer Engineering · Sem 7 (Departmental Elective-IV)

Syllabus

5 units
Unit1

Unit 1: INTRODUCTION

Introduction–Definition – Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.

Unit2

Unit 2: PROBLEM SOLVING METHODS

Problem solving Methods – Search Strategies- Uninformed – Informed – Heuristics – Local Search Algorithms and Optimization Problems – Searching with Partial Observations – Constraint Satisfaction Problems – Constraint Propagation – Backtracking Search – Game Playing – Optimal Decisions in Games – Alpha – Beta Pruning – Stochastic Games

Unit3

Unit 3: KNOWLEDGE REPRESENTATION

First Order Predicate Logic – Prolog Programming – Unification – Forward Chaining-Backward Chaining – Resolution – Knowledge Representation – Ontological Engineering-Categories and Objects – Events – Mental Events and Mental Objects – Reasoning Systems for Categories – Reasoning with Default Information

Unit4

Unit 4: SOFTWARE AGENTS

Architecture for Intelligent Agents – Agent communication – Negotiation and Bargaining – Argumentation among Agents – Trust and Reputation in Multi-agent systems.

Unit5

Unit 5: APPLICATIONS

AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware – Perception – Planning – Moving

Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Understand the basics of the theory and practice of Artificial Intelligence as a discipline and about intelligent agents.K2
  2. CO2Understand search techniques and gaming theory.K2
  3. CO3Apply knowledge representation techniques and problem-solving strategies to common AI applications.K3
  4. CO4Aware of techniques used for classification and clustering.K2
  5. CO5Understand the basics of pattern recognition and steps required for it.K2

Text books

  1. S. Russell and P. Norvig, “Artificial Intelligence: A Modern Approach‖, Prentice Hall, Third Edition, 2009.
  2. Bratko, “Prolog: Programming for Artificial Intelligence”, Fourth edition, Addison-Wesley Educational Publishers Inc., 2011.
  3. M. Tim Jones, ―Artificial Intelligence: A Systems Approach(Computer Science)‖, Jones and Bartlett Publishers, Inc.First Edition, 2008
  4. Nils J. Nilsson, ―The Quest for Artificial Intelligence‖, Cambridge University Press, 2009.
  5. William F. Clocksin and Christopher S. Mellish,‖ Programming in Prolog: Using the ISO Standard‖, Fifth Edition, Springer, 2003.
  6. Gerhard Weiss, ―Multi Agent Systems‖, Second Edition, MIT Press, 2013.
  7. David L. Poole and Alan K. Mackworth, ―Artificial Intelligence: Foundations of Computational Agents‖, Cambridge University Press, 2010.

Official AKTU syllabus

This subject is on page 14 of the original AKTU PDF.

Official AKTU syllabus PDF ↗