Intelligent Systems – Architecture, Design And Control

By (author) Alexander M. Meystel; By (author) Meystel, AM
Short description/annotation
A treatment of the field of intelligent systems, this book examines the theoretical and practical aspects of these systems. It focuses on the NIST-RCS (Real-time Control System) model, that has been used in the Mars Rover.
Description
This comprehensive treatment of the field of intelligent systems is written by two of the foremost authorities in the field. The authors clearly examine the theoretical and practical aspects of these systems. The book focuses on the NIST-RCS (Real-time Control System) model, that has been used recently in the Mars Rover.
Table of contents
PREFACE. 1. INTELLIGENCE IN NATURAL AND CONSTRUCTED SYSTEMS. 1.1. Introduction. 1.2. Brief Overview of the Evolving Concepts of Mind and Intelligence. 1.3. Intelligent Systems: Can We Distinguish Them from Nonintelligent Systems? 1.4. Intelligence: Product and Tool of Behavior and Communication. 1.5. Evolution of Automatisms. 1.6. From Agent to Multiscale Communities of Agents. 1.7. Cognitive Agents and Architectures. References. Problems. 2. THEORETICAL FUNDAMENTALS. 2.1. Mathematical Framework of the Architectures for Intelligent Systems. 2.2. Formal Model of Intelligent Systems and Processes. 2.3. Necessary Terminology and Assumptions. 2.4. Construction and Properties of Objects. 2.5. Extracting Entities from Reality. 2.6. Grouping + Filtering + Search: The Elementary Unit of Self--Organization. 2.7. Relative Intelligence and Its Evolution. 2.8. On the Resemblances among Processes of Structuring in Nature and Representation. 2.9. Semiotic Framework of the Architectures for Intelligent Systems. References. Problems. 3. KNOWLEDGE REPRESENTATION. 3.1. Problem of Representing the Natural World. 3.2. What Is Knowledge? 3.3. Knowledge Representation in the Brain: Acquiring Automatisms. 3.4. Sensory and Symbolic Representations in the Brain. 3.5. Reference Frame, Imagination, and Insight. 3.6. Principles of Knowledge Representation, Entities, and Relational Structures. 3.7. Multiresolutional Character of Knowledge and Its Complexity. 3.8. Virtual Phenomena of Knowledge Representation. References. Problems. 4. REFERENCE ARCHITECTURE. 4.1. Components of a Reference Architecture. 4.2. Evolution of the Reference Architecture for Intelligent Systems. 4.3. Hierarchy with Horizontal "In Level" Connections. 4.4. Levels of Resolution. 4.5. Neural Components of the Architecture. 4.6. Behavior--Generating Hierarchy. 4.7. Analysis of Multiresolutional Architectures. 4.8. Agent--Based Reference Architectures. References. Problems. 5. MOTIVATIONS, GOALS, AND VALUE JUDGMENT. 5.1. Internal Needs versus External Goals. 5.2. Value Judgments. 5.3. Achieving the Goal: Optimization via the Calculus of Variations. References. Problems. 6. SENSORY PROCESSING. 6.1. In--level and Inter--level Processes. 6.2. Sensory Processing as a Module of the Level. 6.3. Hierarchy of Sensory Processing. 6.4. Multiresolutional Nature of Sensory Processing. References. Problems. 7. BEHAVIOR GENERATION. 7.1. Preliminary Concepts of Multiresolutional Behavior Generation. 7.2. BG Architecture. 7.3. Strategy of Multiresolutional Control: Generation of a Nested Hierarchy. 7.4. Overall Organization of Behavior Generation. 7.5. PLANNER. 7.6. EXECUTOR: Its Structure and Functioning. 7.7. Conclusions: Integrating BG in the Intelligent System. References. Problems. 8. MULTIRESOLUTIONAL PLANNING: A SKETCH OF THE THEORY. 8.1. Introduction to Planning. 8.2. Emerging Problems in Planning. 8.3. Planning of Actions and Planning of States. 8.4. Linkage between Planning and Learning. 8.5. Planning in Architectures of Behavior Generation. 8.6. Path Planning in a Multidimensional Space. 8.7. Multiresolutional Planning as a Tool of Increasing Efficiency of Behavior Generation. References. Problems. 9. MULTIRESOLUTION