Foundations of Intelligent Knowledge-Based Systems

Foundations of Intelligent Knowledge-Based Systems

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The construction of intelligent machines is the primary goal of research in artificial intelligence and knowledge-based systems. This book is designed to introduce the foundations of mathematical and philosophical approaches to this rapidly expanding research area.
Foundations of Intelligent Knowledge-Based Systems is divided into three parts. Part I uses logic as a guideline and addresses fundamental theoretical and practical issues in developing large scale intelligent knowledge-based systems (IKBS). PartII discusses modal and intentional logic, nonmonotonic logic, induction and reasoning under uncertainty, and also covers advanced concepts such as planning, actions, states, and temporal systems. Part III looks at the architecture and design principles ofIKBSs using a case study, thus illuminating many of the principles and concepts developed in Parts I and II.
This text presents a unified and rigorous study of IKBS theory and application. It is essential reading for advanced undergraduates, graduates, and developers in knowledge-based systems, artificial intelligence, and expert systems.
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Product details

  • Hardback | 507 pages
  • 174 x 248.7 x 32.3mm | 1,064.96g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 0126960607
  • 9780126960600

Table of contents

Part I: Introduction: Background, Historical Developments, and Bibliography. Declarative Knowledge: Propositional Logic. Predicate Logic. Declarative Semantics. Clausal Form. Deduction and Inference: Meaning and Interpretation. Model--Theoretic and Proof, Theoretic Approaches. Query Evaluation. Proof Tree. Inference Procedures. Automated Reasoning Systems: Theoron Provers. Substitution and Unification. Resolution. Resolution Strategies. Rewrite Rules. Logic Programming and Deductive Data Bases. Frames, Semantic Nets, and Production Systems: Frame Structure. Slots--Assertions. ISA--Hierarchy. Inference with Frames. Production Systems. Computation Methods. Search: General: Search Algorithm. Domain Specific Search. Semantic Information and Strategies to Control the Search. Part II: Modal and Intentional Logic: Propositional Modal Logic. Predicate Modal Logic. Modal Structure, Kripke Structure. Modal Operation. IntentionalLogic. Nonmonotonic Reasoning: Nonmonotonic Logic. The Closed-World Assumption. Negation by Failure. Circumscription. Computational Model of Nonmonotonic Logic. Induction: Basic Properties. Concept Formation. Generalization and Specialization. Matching. Learning. Uncertainty: Probabilities. Bayes Law. Fuzzy Logic. Probabilistic Logic. Computation. Meta Knowledge. Temporal Systems. Planning Actions: States, Actions, and the Frame Problem. Action Ordering. A Basic Plan Interpreter. Conditional Plans. Goals, Restricted Goals. Goal Regression. Domains and Application. Decision Theory. Part III: Architecture of IKBS: Components. Data Flow. Control Flow. Case Study PAYE Tax System: Introduction and Basic Properties. Temporal Aspect. Architecture of PAYE. Design of PAYE. Computational Model. Execution. The Link to Imperative Systems. Knowledge Acquisition. The Future: Parallel Systems. Intelligent Systems.
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