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ARTIFICIAL INTELLIGENCE

Theory (100) Practical (50)

INTRODUCTION TO ARTIFICIAL INTELLIGENCE

History of Artificial Intelligence, Importance of Artificial Intelligence, Application of Artificial Intelligence.

KNOWLEDGE BASED SYSTEMS

Knowledge general concepts, Importance of Knowledge, Representation of Knowledge, Knowledge organization, Manipulations and acquisition of Knowledge,

PREDICATE CALCULUS

Predicate prepositional Logic, Properties of wwfs, horn clauses, syntax and semantic for prepositional logic,

SEARCH SPACE

Depth breadth and best searching techniques, backward and forward searches, uniformed and blind searches

NATURAL LANGUAGE PROCESSING

Natural Language Generation, Natural Language Problem, Basic parsing techniques, morphological and syntactical analysis, semantic, discourse integration and Pragmatic analyses

EXPERT SYSTEM

Architecture of ES, Application of ES, Ten development phases of ES, Dealing with uncertainty, heuristics, Knowledge based, representation system, Knowledge engineering languages.

COMPUTER VISION AND ROBOTICS

Intelligent Robots, Mobile Robots, Parts of Robots, Servo and Nonservo Control, Visual Clues: Color, Depth, Texture, Object Recognition

MACHINE LEARNING

Human neuron perception, single and multiple layered neural network, Feed forward neural network, intelligent editor, introduction and applications of genetic programming

 

CONCEPTS OF PROGRAMMING LANGUAGE OF ARTIFICIAL

INTELLIGENCE

Introduction to Prolog and Lisp Language, Built-in Predicates, Demonstration of Artificial Intelligence by simple code in Lisp & Prolog

PATTERN RECOGNITION

Recognition and Classification Process, Learning Classification Patterns, Recognizing and Understanding Speech

REFERENCE BOOKS

[1] Henry C Mishkoff, “Understanding Artificial Intelligence”

[2] Carl Townsend, “Turbo Prolog”

[3] Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”

[4] George Fluger, William A. Stubb Lefield, “Artificial Intelligence”

 

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