Introduction to Intelligence and Expert Systems

By:

Patterson, Dan W

Material type: Text

TextPublication details: Noida Pearson 2025Description: xv, 448p. 24 x 18 cmISBN:

9789332551947

DDC classification:

006.3 PAT

Summary: Part 1: Introduction to Artificial Intelligence - Overview of Artificial Intelligence Knowledge: General Concepts LISP and Other AI Programming Languages Part 2: Knowledge Representation - Formalized Symbolic Logics Dealing with Inconsistencies and Uncertainties Probabilistic Reasoning Structured Knowledge: Graphs, Frames and Related Structures Object Oriented Representations Part 3: Knowledge Organization and Manipulation - Search and Control Strategies Matching Techniques Knowledge Organization and Management Part 4: Perception, Communication and Expert Systems - Natural Language Processing Pattern Recognition Visual Image Understanding Expert Systems Architectures Part 5: Knowledge Acquisition - General Concepts in Knowledge Acquisition Early Work in Machine Learning Learning by Induction Examples of Other Inductive Learners Analogical and Explanation Based Learning

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Reference	Raj Kumar Goel Institute of Technology	AIML (Artificial Intelligence and Machine Learning)	006.3 PAT (Browse shelf(Opens below))	Not for loan		96287
Reference	Raj Kumar Goel Institute of Technology	AIML (Artificial Intelligence and Machine Learning)	006.3 PAT (Browse shelf(Opens below))	Not for loan		96288

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Previous	006.3 KHE First Course in Artificial Intelligence	006.3 NIL Artificial Intelligence	006.3 NIL Artificial Intelligence	006.3 PAT Introduction to Intelligence and Expert Systems	006.3 PAT Introduction to Intelligence and Expert Systems	006.3 RAJ Neural Networks, Fuzzy Systems, and Evolutionary Algorithms Synthesis and Applications	006.3 RAJ Neural Networks, Fuzzy Systems, and Evolutionary Algorithms Synthesis and Applications	Next

Part 1: Introduction to Artificial Intelligence - Overview of Artificial Intelligence
Knowledge: General Concepts
LISP and Other AI Programming Languages
Part 2: Knowledge Representation - Formalized Symbolic Logics
Dealing with Inconsistencies and Uncertainties
Probabilistic Reasoning
Structured Knowledge: Graphs, Frames and Related Structures
Object Oriented Representations
Part 3: Knowledge Organization and Manipulation - Search and Control Strategies
Matching Techniques
Knowledge Organization and Management
Part 4: Perception, Communication and Expert Systems - Natural Language Processing
Pattern Recognition
Visual Image Understanding
Expert Systems Architectures
Part 5: Knowledge Acquisition - General Concepts in Knowledge Acquisition
Early Work in Machine Learning
Learning by Induction
Examples of Other Inductive Learners
Analogical and Explanation Based Learning

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Introduction to Intelligence and Expert Systems

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