• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Ljudböcker
  • Pocketböcker
  • Spel och pussel

5% studentrabatt – använd koden KURSBOK27 →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Data och IT
    2. Informationsteknik: allmänt

    Computational Experiments

    A Bridge between Artificial Intelligence and Social Sciences

    AvXiao Xue,Fei-Yue Wang

    Inbunden, Engelska, 2026

    1 719 kr

    Kommande

    Beskrivning

    A methodological framework for bridging the gap between Artificial Intelligence and Social Sciences Complex cyber-physical-social systems demand rigorous analysis, design, regulation and validation methods that traditional approaches cannot provide. Computational Experiments: A Bridge between Artificial Intelligence and Social Sciences delivers a systematic methodology spanning modeling, simulation, and validation of intelligent systems. Written by leading researchers in complex systems and artificial intelligence, this work provides both theoretical foundations and practical frameworks for studying intricate social and physical systems. The book covers the artificial society modeling framework across four levels: AI agents and prospect theory, learning mechanisms of AI agents, AI society and social networks, and integration with environmental systems. It addresses how computational experiments incorporate generative agents and large language models, and explores policy sandboxes for decision analysis and social system behavior prediction in complex contexts. The book also discusses: Comprehensive coverage of computational experiment methodology including origins, development history, and knowledge frameworks essential for practical applicationsSocial simulation technology foundations providing unique insights into simulating and deducing complex social systems from interdisciplinary research perspectivesDetailed exploration of AI agent architectures incorporating prospect theory, ??reinforcement learning mechanisms, and multi-agent coordination strategies for ??system modelingFrameworks for integrating virtual and real-world intelligence to improve predictive capabilities and support decision-making in complex operational environmentsDesigned for professors, researchers, and graduate students in computer science, artificial intelligence, social computing, and systems engineering, this book also serves professionals in policy simulation, strategic planning, and smart system development who require rigorous methods for validating intelligent system behavior.

    Produktinformation

    • Utgivningsdatum:2026-08-13
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:544
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394377459

    Utforska kategorier

    • Informationsteknik: allmänt inom Data och IT
    • Tillämpad datateknik inom Data och IT
    • Artificiell intelligens inom Data och IT

    Mer om författaren

    Xiao Xue, PhD, is a Professor in the School of Software, College of Intelligence and Computing, at Tianjin University. He has authored three academic books and over 50 articles in prestigious international journals including the IEEE Transactions series. He serves as Associate Editor for IEEE Transactions on Intelligent Vehicles, International Journal of Crowd Science, and Complex System Modeling and Simulation. Fei-Yue Wang, PhD, is Director of the State Key Laboratory for Management and Control of Complex Systems at the Chinese Academy of Sciences, where he founded the Intelligent Control and Systems Engineering Center. He is an IEEE Fellow, AAAS Fellow, ASME Fellow, IFAC Fellow, INCOSE Fellow, and Outstanding Scientist of ACM. He serves as Editor-in-Chief of several IEEE Transactions and journals.

    Innehållsförteckning

    • About the Author xvPreface xvii1 Origin and Goal of Computational Experiments 11.1 Complexity Science 11.2 Methodological Framework of Computational Experiments 161.3 Organizational Structure of the Book 251.4 Chapter Summary 312 Computational Experiments for Physical Systems 372.1 The Principle of Similarity and System Modeling 372.2 Simulation Examples and Concepts 462.3 Experimental Theory 582.4 Statistical Methods 662.5 Chapter Summary 723 Computational Experiments for Social Systems 753.1 Social Simulation Method 753.2 Simulation of Social Systems 913.3 Causal Inference 1043.4 A Classic Case of Social Simulation 1113.5 Chapter Summary 1264 Methodological Framework of Computational Experiments 1334.1 Framework of Computational Experiment Method 1334.2 Computational Experiment Platform Architecture 1414.3 Operation Steps of the Experimental Platform 1514.4 Chapter Summary 1685 The First Step — Building an Artificial Society 1715.1 Analysis of Characteristics of Artificial Society 1715.2 The Modeling Framework of Artificial Society 1775.3 The Modeling Framework of Artificial Society 1845.4 Case Study: Intelligent Logistics System 1905.5 Chapter Summary 1996 The Second Step — Constructing the Experimental System 2036.1 From Game Worlds to Virtual Societies 2036.2 Virtual Experiments with Humans Outside the Loop 2116.3 Model Integration of Social Simulators 2146.4 Case Study 2246.5 Chapter Summary 2327 The Third Step—Experimental Design and Generative Explanation 2357.1 Comprehensive Framework of Computational Experiment Design 2367.2 Introduction to Experimental Design Methods 2437.3 Design of Scenario Generation Algorithm 2557.4 Case Study: API Service Market 2657.5 Chapter Summary 2738 The Fourth Step — Experimental Analysis and Causal Inference 2798.1 The Laws of System Complexity 2798.2 Causal Inference Framework of Computational Experiments 2878.3 Causal Inference Layers in Computational Experiments 2988.4 Case Study: Algorithmic Behavior on Internet Platforms 3078.5 Chapter Summary 3179 The Fifth Step — Maturity Evaluation of Computational Experiments 3219.1 Theoretical Foundation of Computational Experiment Validation 3229.2 Model Evaluation Framework in Computational Epidemiology 3329.3 Capability Maturity of Computational Epidemiological Models 3379.4 Case Study of Computational Epidemiological Models 3479.5 Chapter Summary 35610 LLM-Based Agents and Social Simulation 36110.1 The Architecture of LLM-Based Agent 36210.2 Stanford Smallville 37110.3 LLM-Based Agent's Capability Pool 38010.4 Applications of LLM-Based Agent Simulation 39010.5 Chapter Summary 40111 Large Language Model Agents and Workflow 40711.1 Collaboration Framework of AI Agents 40811.2 The Orchestration Methods of Multiagents 42011.3 Automation of Computational Experiments 43011.4 The Challenges of Multiagent Collaboration 43811.5 Chapter Summary 44712 Roadmap of Computational Experiment Method 45112.1 Roadmap of Computational Experiment Method 45112.2 Q1: How to Conduct Computational Modeling of the Real World 45412.3 Q2: How to Conduct Causal Reasoning in a Virtual World 45612.4 Q3: How to Ensure That Experimental Laws Hold in Reality? 46112.5 Traditional Simulation vs. Generative Simulation 46312.6 Chapter Summary 468References 468A Appendix 471Index 511