智能系统
2003-11
电子工业出版社
梅斯特
696
1002000
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智能是一个很难理解的概念，在生物学和人工智能系统领域，对智能机制和功能的研究不断扩大。本书介绍了智能系统的最初的模型，把多种来源的知识综合到一起，开发了一种理论，可以用来分析从经济到集成制造领域的所有高级的复杂系统。本书重点在智能作为一种多解决方案中的计算现象，希望大大影响在智能范围内的未来研究和发展。它是科学家、工程师和希望探索当代理论和计算智能工具的宝贵资源。
Alexander M.Meystel，宾夕法尼亚州费城Drexel大学电气和计算机工程系的教授。
James S.Albus，美国国家标准技术研究所智能系统分部的高级院士。
1 INTELLIGENCE IN NATUAL AND CONSTRUCTED SYSTEMS 1.1 Introduction,1 1.2 Brief Overview of the Evolving Concepts of Mind and Intelligence,4 1.3 Intelligent Systems:Can We Distinguish Them from Nonintelligent Systems?,12 1.4 Intelligenct:Product and Tool of Behavior and Communication,16 1.5 Evoluton of Automatisms,20 1.6 From Agent to Multiscale Communities of Agents,24 1.7 Cognitive Agents and Architectures,29 References,32 Problems,362 THEORETICAL FUNDAMENTALS 2.1 Mathematical Framework of the Architectures for Intelligent Systems,38 2.2 Formal Model of Intelligent Systems and Processes, 42 2.3 Necessary Terminology and Assumptions,60 2.4 Construction and Properties of Objects,67 2.5 Extracting Entities from Reality ,70 2.6 Grouping+Filtering+Search:The Elementary Unit of Self-Organzation,80 2.7 Relative Intelligence and Its Evolution,83 2.8 On the Resemblances among Processes of Structuring in Nature and resentation,87 2.9 Semiotic Framework of the Architectures for Intelligent Systems,893 KNOWLEDGE REPRESENTATION 3.1 Problem of Representing the Natural Worle,100 3.2 What Is Knowledge?，108 3.3 Kowledge Representation in the Brain:Acquiring Automatisms,115 3.4 Sensory and Sybolic Representations i the Brain,117 3.5 Refernce Frame,Imagination,and Insight,120 3.6 Principles of Konwledge Representation,Entities ,and Relational Structures,121 3.7 Multiresolutional Character of Knowledge and Its Complexity,147 3.8 Virtual Phenomena of Knowledge Representation,1514 REFERENCE ARCHITECTURE 4.1 Components of a Reference Architecture,158 4.2 Evolution of the Reference Architecture for Intelligent Systems,160 4.3 Hierarchy with Horizxontal "In Level "Connections,163 4.4 Levels of Resolution,165 4.5 Neural Components of the Architecture,169 4.6 Behavior-Generating Hierarchy,171 4.7 Analysis of Multiresolutional Architectures,172 4.8 Agent-Basesd Refernce Architectures,1805 MOTIVATIONS,GOALS,AND VALUE JUDGMENT 5.1 Intermal Needs versus External Goals,188 5.2 Value Judgments,199 5.3 Achieving the Goal :Optimization via the Calculus of Variations,2076 SENSORY PROCESSING 6.1 In-level and Inter-level Processes,220 6.2 Sensory Processing as a Module of the Level ,228 6.3 Hierarchy of Sensory Processing,238 6.4 Multiresolutional Nature of Sensory Processing ,2517 BEHAVIOR GENERATION 7.1 Preliminary Concepts of Multiresolutional Behavior Generation,257 7.2 BG Architecture,265 7.3 Srategy of Multiresolutional Control:Generation of a Nested Hierarchy,273 7.4 Overall Organization of Behavior Generation,285 7.5 PLANNER,309 7.6 EXECUTOR :Its Structure and Functioning,330 7.7 Conclusions:Integrating BG in the Intelligent System,3378 MULTIRESOLUTIONAL PLANNING:A SKETCH OF THE THEORY 8.1 Introduction to Planning,343 8.2 Emerging Problems in Planning, 349 8.3 Planning of Actions and Planning of States,354 8.4 Linkage between Planning and Learning,357 8.5 Planning in Architectures of Behavior Generation,358 8.6 Path Planning in a Multidimensional Space,36 8.7 Multiresolutional Planning as a Tool of Increasing Efficiency of Behavior Generation,3739 MULTIRESOLUTIONAL HIERARCHY OF PLANNER/EXECUTOR MODULES10 LEARNING11 APPLICATIONS OF MULTIRESOLUTIONAL ARCHITECTURES FOR INTELLIGENT SYSTEMS12 INTELLIGENT SYSTEMS:PRECURSOR OF THE NEW PARADIGM IN SCIENCE AND NEGINEERING
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