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Introduction to artificial intelligence and expert systems/ Dan W. Patterson.

By: Patterson, Dan WMaterial type: Text

TextPublication details: New Delhi: PHI Learning Private Limited, 1990Description: xv, 448 p ill. 25 cmISBN: 9788120307773Subject(s): Artificial intelligence | Expert systems (Computer science)DDC classification: 006.338

Contents:

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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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
General Books	Central Library, Sikkim University	006.338 PAT/I (Browse shelf(Opens below))	Available		P18680

Total holds: 0

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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