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AKTU Artificial Intelligence (BCIT054) Syllabus PDF – B.Tech 3rd Year

Artificial Intelligence BCIT054

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  • Semester 5
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Official AKTU syllabus of Artificial Intelligence (BCIT054) for B.Tech 3rd Year – 3 credits, L-T-P 3-0-0. 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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BCIT054 · 3 credits · L-T-P 3-0-0

Course Outcomes

At the end of course, the student will be able to understand

CO 1Understand the basics of the theory and practice of Artificial Intelligence as a discipline and about intelligent agents.K 2
CO 2Understand search techniques and gaming theory.K , K 2 3
CO 3The student will learn to apply knowledge representation techniques and problem solving strategies to common AI applications.K , K 3 4
CO 4Student should be aware of techniques used for classification and clustering.K , K 2 3
CO 5Student should aware of basics of pattern recognition and steps required for it.K , K 2 4

Course Content

L-T-P: 3-0-0

UnitTopicProposed Lecture
IINTRODUCTION : Introduction–Definition – Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.08
IIPROBLEM 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 Games08
IIIKNOWLEDGE 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 Information08
IVSOFTWARE AGENTS Architecture for Intelligent Agents – Agent communication – Negotiation and Bargaining – Argumentation among Agents – Trust and Reputation in Multi-agent systems.08
VAPPLICATIONS AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware – Perception – Planning – Moving08

Text 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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