Artificial Intelligence Mechatronics 8th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective IV) detail syllabus for Mechatronics Engineering (Mechatronics), 2017 regulation is collected from the Anna Univ official website and presented for students of Anna University. The details of the course are: course code (CS8691), Category (PE), Contact Periods/week (3), Teaching hours/week (3), Practical Hours/week (0). The total course credits are given in combined syllabus.
For all other mechatronics 8th sem syllabus for be 2017 regulation anna univ you can visit Mechatronics 8th Sem syllabus for BE 2017 regulation Anna Univ Subjects. For all other Professional Elective IV subjects do refer to Professional Elective IV. The detail syllabus for artificial intelligence is as follows.
Course Objective:
- To understand the various characteristics of Intelligent agents
- To learn the different search strategies in AI
- To learn to represent knowledge in solving AI problems
- To understand the different ways of designing software agents
- To know about the various applications of AI.
Unit I
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Unit 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
Unit 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
Unit IV
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Unit V
Applications
AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware – Perception – Planning – Moving
Course Outcome:
Upon completion of the course, the students will be able to:
- Use appropriate search algorithms for any AI problem
- Represent a problem using first order and predicate logic
- Provide the apt agent strategy to solve a given problem
- Design software agents to solve a problem
- Design applications for NLP that use Artificial Intelligence.
Text Books:
- 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.
References:
- M. Tim Jones, Artificial Intelligence: A Systems Approach(Computer Science), Jones and Bartlett Publishers, Inc.; First Edition, 2008
- 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.
- 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.
For detail syllabus of all other subjects of BE Mechatronics, 2017 regulation do visit Mechatronics 8th Sem syllabus for 2017 Regulation.
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