智能系統(tǒng)

內(nèi)容概要

　　 智能是一個(gè)很難理解的概念，在生物學(xué)和人工智能系統(tǒng)領(lǐng)域，對(duì)智能機(jī)制和功能的研究不斷擴(kuò)大。本書介紹了智能系統(tǒng)的最初的模型，把多種來(lái)源的知識(shí)綜合到一起，開(kāi)發(fā)了一種理論，可以用來(lái)分析從經(jīng)濟(jì)到集成制造領(lǐng)域的所有高級(jí)的復(fù)雜系統(tǒng)。本書重點(diǎn)在智能作為一種多解決方案中的計(jì)算現(xiàn)象，希望大大影響在智能范圍內(nèi)的未來(lái)研究和發(fā)展。它是科學(xué)家、工程師和希望探索當(dāng)代理論和計(jì)算智能工具的寶貴資源。

作者簡(jiǎn)介

Alexander M.Meystel，賓夕法尼亞州費(fèi)城Drexel大學(xué)電氣和計(jì)算機(jī)工程系的教授。
   
   James S.Albus，美國(guó)國(guó)家標(biāo)準(zhǔn)技術(shù)研究所智能系統(tǒng)分部的高級(jí)院士。

書籍目錄

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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