Häftad, Engelska, 2027

The Social Optimization of Collective Judgment

A Multiobjective Framework from Consensus to Human-Machine Collaboration

Av Zhen-Song Chen, Xian-Jia Wang

1929 kr

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Beskrivning

The Social Optimization of Collective Judgment: A Multiobjective Framework from Consensus to Human-Machine Collaboration presents a unified treatment of expert judgment aggregation under uncertainty. The book demonstrates how a broad family of optimization-based aggregation methods can be understood within a single framework built on simplex-constrained quantile averaging. It develops aggregation models that progressively incorporate consensus, fairness, social welfare, altruism, reproducibility, scalability, and human-machine collaboration, providing both theoretical foundations and practical implementation guidance.

The book begins with the foundations of classical pooling and optimization-driven aggregation before developing socially grounded aggregation methods that incorporate fairness, welfare, and altruistic objectives. It then addresses scalable and reproducible optimization techniques, including hierarchical aggregation and convex reformulations. A dedicated chapter examines the integration of large language models as virtual experts within auditable decision processes. Five worked case studies apply the framework to building information modeling and digital twin maturity assessment, digital transformation barriers, rail transit accessibility, and human-machine forecasting, followed by a discussion of challenges, open problems, and future research directions.

The book will be valuable to researchers and graduate students in decision analysis, operations research, group decision-making, computational intelligence, forecasting, and social choice; data scientists and machine learning researchers working on calibration and ensemble methods; policy analysts, public administration specialists, engineers, economists, finance professionals, transportation researchers, and public health analysts who require transparent and reproducible approaches to combining expert judgments under uncertainty.

Provides a unified optimization framework and problem-to-model selection guide for choosing appropriate aggregation methods across decision contexts
Delivers reproducible and scalable computational approaches, including convex reformulations and hierarchical aggregation for large stakeholder groups
Enables auditable human-machine collaboration by admitting large language models as virtual experts, with leave-one-out contribution diagnostics and governance of failure modes

Produktinformation

Utgivningsdatum: 2027-06-01
Mått: 152 x 229 x undefined mm
Format: Häftad
Språk: Engelska
Antal sidor: 295
Förlag: Elsevier Science
ISBN: 9780443583148

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Mer information

Zhen-Song Chen (Senior Member, IEEE) received a Ph.D. in traffic and transportation planning and management from the School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China, in 2016. He is currently an Associate Professor with the School of Civil Engineering, Wuhan University, Wuhan, China, and a Visiting Scholar with the University of Washington, Seattle, WA, USA. He has authored or co-authored more than 200 papers in prestigious journals, including the IEEE Transactions on Systems, Man, and Cybernetics: Systems, the IEEE Transactions on Engineering Management, the IEEE Transactions on Fuzzy Systems, Omega, International Journal of Production Economics, Computers & Operations Research, and more. His current research interests include large language models, human-AI collaboration, decision analysis, multiagent systems, and multiobjective optimization. Dr. Chen serves as an Editorial Board Member or Editorial Review Board Member for the IEEE Transactions on Engineering Management, Automation in Construction, and several other international journals. Xian-Jia Wang received Ph.D. in hydrology and water resources engineering from Wuhan University in 1992. He was a Postdoctoral Researcher with the Systems Engineering Institute, Huazhong University of Science and Technology, and with Wuhan University. He was a Senior Researcher and a Visiting Professor with the City University of Hong Kong and The Chinese University of Hong Kong, and a Senior Visiting Scholar with Harvard University, USA, and the University of Newcastle, Australia. He is currently a Professor with the School of Economics and Management, Wuhan University. He has published extensively in international journals and conference proceedings, including Applied Mathematics and Computation, Chaos, Solitons & Fractals, and Knowledge-Based Systems. His current research interests include evolutionary game theory, decision analysis, and investment management. Prof. Wang serves as an Editorial Board Member or Editorial Advisory Board Member of Acta Mathematica Scientia, Systems Engineering—Theory & Practice, and ENGINEERING Management.

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