| 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。本书适用于大学研究生、科学家、工程技术和对智能研究感兴趣的人士。 |
| 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,36 2 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,89 3 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,151 4 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,180 5 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,207 6 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 ,251 7 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,337 8 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,373 9 MULTIRESOLUTIONAL HIERARCHY OF PLANNER/EXECUTOR MODULES 10 LEARNING 11 APPLICATIONS OF MULTIRESOLUTIONAL ARCHITECTURES FOR INTELLIGENT SYSTEMS 12 INTELLIGENT SYSTEMS:PRECURSOR OF THE NEW PARADIGM IN SCIENCE AND NEGINEERING |
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