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AKTU Artificial Intelligence (BAI501) Syllabus PDF – B.Tech 3rd Year
Artificial Intelligence BAI501
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Official AKTU syllabus of Artificial Intelligence (BAI501) for B.Tech 3rd Year. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Artificial Intelligence
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Course Outcomes
At the end of course , the student will be able to understand
| CO 1 | Understand the basics of the theory and practice of Artificial Intelligence as a discipline and about intelligent agents. | K 2 |
| CO 2 | Understand search techniques and gaming theory. | K , K 2 3 |
| CO 3 | The student will learn to apply knowledge representation techniques and problem solving strategies to common AI applications. | K , K 3 4 |
| CO 4 | Student should be aware of techniques used for classification and clustering. | K , K 2 3 |
| CO 5 | Student should aware of basics of pattern recognition and steps required for it. | K , K 2 4 |
Course Content
L-T-P: 3-0-0
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | INTRODUCTION : Introduction–Definition – Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems. | 08 |
| II | 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 | 08 |
| III | 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 | 08 |
| IV | SOFTWARE AGENTS Architecture for Intelligent Agents – Agent communication – Negotiation and Bargaining – Argumentation among Agents – Trust and Reputation in Multi-agent systems. | 08 |
| V | APPLICATIONS AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware – Perception – Planning – Moving | 08 |
Text Books
1.S. Russell and P. Norvig, “Artificial Intelligence: A Modern Approach‖, Prentice Hall, Third Edition, 2009.
- I. Bratko, ―Prolog: Programming for Artificial Intelligence‖, Fourth edition, Addison-Wesley Educational Publishers Inc., 2011.
- 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.
- 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.
- David L. Poole and Alan K. Mackworth, ―Artificial Intelligence: Foundations of Computational Agents‖, Cambridge University Press, 2010.
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