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Description:
This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence that is suitable as a textbook. The book provides detailed coverage of basic topics as well as several closely related ones.
Unlike traditional textbooks, the book brings together many leading experts, guaranteeing a broad and diverse base of knowledge and expertise. It emphasizes aspects of both theory and application, and provides many illustrations and examples. Also included are thought-provoking exercises of varying degrees of difficulty and a twenty-page glossary of terms found in the study of agents, multiagent systems, and distributed artificial intelligence.
The book can be used for teaching as well as self-study, and is designed to meet the needs of both researchers and practitioners. In view of the interdisciplinary nature of the field, it will be a useful reference not only for computer scientists and engineers, but for social scientists and management and organization scientists as well.
Table of Contents:
Contributing Authors Preface Prologue PART I: BASIC THEMES 1 Intelligent Agents 1.1 Introduction 1.2 What Are Agents? 1.2.1 Examples of Agents 1.2.2 Intelligent Agents 1.2.3 Agents and Objects 1.2.4 Agents and Expert Systems 1.3 Abstract Architectures for Intelligent Agents 1.3.1 Purely Reactive Agents 1.3.2 Perception 1.3.3 Agents with State 1.4 Concrete Architectures for Intelligent Agents 1.4.1 Logic-Based Architectures 1.4.2 Reactive Architectures 1.4.3 Belief-Desire-Intention Architectures 1.4.4 Layered Architectures 1.5 Agent Programming Languages 1.5.1 Agent-Oriented Programming 1.5.2 Concurrent METATEM 1.6 Conclusions 1.7 Exercises 1.8 References 2 Multiagent Systems and Societies of Agents 2.1 Introduction 2.1.1 Motivations 2.1.2 Characteristics of Multiagent Environments 2.2 Agent Communications 2.2.1 Coordination 2.2.2 Dimensions of Meaning 2.2.3 Message Types 2.2.4 Communication Levels 2.2.5 Speech Acts 2.2.6 Knowledge Query and Manipulation Language (KQML) 2.2.7 Knowledge Interchange Format (KIF) 2.2.8 Ontologies 2.2.9 Other Communication Protocols 2.3 Agent Interaction Protocols 2.3.1 Coordination Protocols 2.3.2 Cooperation Protocols 2.3.3 Contract Net 2.3.4 Blackboard Systems 2.3.5 Negotiation 2.3.6 Multiagent Belief Maintenance 2.3.7 Market Mechanisms 2.4 Societies of Agents 2.5 Conclusions 2.6 Exercises 2.7 References 3 Distributed Problem Solving and Planning 3.1 Introduction 3.2 Example Problems 3.3 Task Sharing 3.3.1 Task Sharing in the Toll Problem 3.3.2 Task Sharing in Heterogeneous Systems 3.3.3 Task Sharing for DSNE 3.3.4 Task Sharing for Interdependent Tasks 3.4 Result Sharing 3.4.1 Functionally Accurate Cooperation 3.4.2 Shared Repositories and Negotiated Search 3.4.3 Distributed Constrained Heuristic Search 3.4.4 Organizational Structuring 3.4.5 Communication Strategies 3.4.6 Task Structures 3.5 Distributed Planning 3.5.1 Centralized Planning for Distributed Plans 3.5.2 Distributed Planning for Centralized Plans 3.5.3 Distributed Planning for Distributed Plans 3.6 Distributed Plan Representations 3.7 Distributed Planning and Execution 3.7.1 Post-Planning Coordination 3.7.2 Pre-Planning Coordination 3.7.3 Interleaved Planning, Coordination, and Execution 3.7.4 Runtime Plan Coordination Without Communication 3.8 Conclusions 3.9 Exercises 3.10 References 4 Search Algorithms for Agents 4.1 Introduction 4.2 Constraint Satisfaction 4.2.1 Definition of a Constraint Satisfaction Problem 4.2.2 Filtering Algorithm 4.2.3 Hyper-Resolution-Based Consistency Algorithm 4.2.4 Asynchronous Backtracking 4.2.5 Asynchronous Weak-Commitment Search 4.3 Path-Finding Problem 4.3.1 Definition of a Path-Finding Problem 4.3.2 Asynchronous Dynamic Programming 4.3.3 Learning Real-Time A* 4.3.4 Real-Time A* 4.3.5 Moving Target Search 4.3.6 Real-Time Bidirectional Search 4.3.7 Real-Time Multiagent Search 4.4 Two-Player Games 4.4.1 Formalization of Two-Player Games 4.4.2 Minimax Procedure 4.4.3 Alpha-Beta Pruning 4.5 Conclusions 4.6 Exercises 4.7 References 5 Distributed Rational Decision Making 5.1 Introduction 5.2 Evaluation Criteria 5.2.1 Social Welfare 5.2.2 Pareto Efficiency 5.2.3 Individual Rationality 5.2.4 Stability 5.2.5 Computational Efficiency 5.2.6 Distribution and Communication Efficiency 商品描述(中文翻譯)
描述:
這是第一本全面介紹多代理系統和當代分散式人工智慧的教科書。該書詳細涵蓋了基本主題以及幾個密切相關的主題。與傳統教科書不同,本書匯集了許多領先的專家,保證了廣泛而多樣的知識和專業技能基礎。它強調理論和應用的各個方面,並提供了許多插圖和範例。此外,還包括了不同難度的引人深思的練習題,以及一個包含二十頁的術語表,涵蓋了代理、代理系統和分散式人工智慧的研究中出現的術語。
本書可用於教學和自學,旨在滿足研究人員和實務工作者的需求。考慮到該領域的跨學科特性,它將成為計算機科學家和工程師,以及社會科學家和管理組織科學家的有用參考資料。
目錄:
貢獻作者
前言
序言
第一部分:基本主題
1 智能代理
1.1 介紹
1.2 什麼是代理?
1.2.1 代理的範例
1.2.2 智能代理
1.2.3 代理與物件
1.2.4 代理與專家系統
1.3 智能代理的抽象架構
1.3.1 純反應代理
1.3.2 感知
1.3.3 具有狀態的代理
1.4 智能代理的具體架構
1.4.1 基於邏輯的架構
1.4.2 反應式架構
1.4.3 信念-欲望-意圖架構類似商品
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