UNIQUE SERIES AKTU Syllabus
BCIT054

Artificial Intelligence

L-T-P3-0-0 Credits3 Session2024-25 TypeTheory
Appears in 3 semesters · 3 branches

B.Tech CSE (Cyber Security) · Sem 5 (Departmental Elective-II) · B.Tech CSE (Internet of Things) · Sem 5 (Departmental Elective-II) · B.Tech Electronics & Computer Engineering · Sem 5 (Department Elective-II)

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Syllabus

5 units · 40 lecture hours
Unit1

Unit 1: INTRODUCTION

8 hrs

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

Unit2

Unit 2

8 hrs

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

8 hrs

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

8 hrs

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

Unit5

Unit 5

8 hrs

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, K3
  3. CO3The student will learn to apply knowledge representation techniques and problem solving strategies to common AI applications.K3, K4
  4. CO4Student should be aware of techniques used for classification and clustering.K2, K3
  5. CO5Student should aware of basics of pattern recognition and steps required for it.K2, K4

Note: The AKTU syllabus PDF of some branches prints this subject with small differences in the course outcomes (Electronics & Computer). Please also check the official AKTU PDF of your branch, linked at the end of your semester page.

Text books7 books
  1. S. Russell and P. Norvig, “Artificial Intelligence: A Modern Approach‖, Prentice Hall, Third Edition, 2009.
  2. I. 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.

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Official AKTU syllabus

This subject is on page 13 of the original AKTU PDF.

Official AKTU syllabus PDF ↗