Introduction to Artificial Intelligence and Expert Systems

This text deals comprehensively with important aspects of artificial intelligence and expert systems. It illustrates the knowledge-system approach and emphasises the relevant use of such knowledge in specific systems. A considerable portion of the text is devoted to the subject of knowledge representation, including methods of dealing with uncertain, incomplete and vague knowledge (e.g. methods related to nonmonotonic logics and commonsense reasoning).The book is divided into five parts related to a detailed analysis of knowledge: Introduction to Artificial Intelligence, Knowledge Representation, Knowledge Organisation and Manipulation, Perception, Communi-cation and Expert Systems and Knowledge Acquisition. Table of Contents Preface. 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. References. Index.