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Influence Models in Group Decision-Making / by Hang Luo.

Springer Nature - Synthesis Collection of Technology (R0) eBook Collection 2026 Available online

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Format:
Book
Author/Creator:
Luo, Hang.
Series:
Synthesis Lectures on Computer Science, 1932-1686
Language:
English
Subjects (All):
Multiagent systems.
Social evolution.
Operations research.
Artificial intelligence.
Social sciences--Data processing.
Social sciences.
Computer science.
Multiagent Systems.
Social Evolution.
Operations Research and Decision Theory.
Artificial Intelligence.
Computer Application in Social and Behavioral Sciences.
Computer Science.
Local Subjects:
Multiagent Systems.
Social Evolution.
Operations Research and Decision Theory.
Artificial Intelligence.
Computer Application in Social and Behavioral Sciences.
Computer Science.
Physical Description:
1 online resource (131 pages)
Edition:
1st ed. 2026.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
Summary:
This book examines influence among decision-makers in group decision-making. It is quite common that people influence and are influenced by each other in group decision-making. Likewise, artificial intelligences can influence and be influenced by each other in interaction or collaboration, and both a person and an artificial intelligence can be called an agent. The author explores how humans or artificial intelligences can interact with and influence each other during the decision-making process, where such influence can reshape the outcome of the group decision. With an interdisciplinary approach, various applications are considered including: computer science (distributed computing, distributed artificial intelligence, particularly multi-agent system); economics and management (joint-stock company voting); and politics (domestic elections and international organization decision-making). The book presents settings of group decision-making where agents’ preferences/choices are influenced (and thus changed) by each other. As the influence of reality faced by an agent usually comes from more than one agent simultaneously, the author provides both cardinal and ordinal approaches, building social influence functions and a matrix influence function, to address multiple sources of influence in group decision-making. To better describe the complex influence in reality, the author provides a framework of the three levels of influence and its mathematical models to address individual, coalitional, and structural influence and their mixed effects in the context of group decision-making. Even though it is not easy to address the influence of structures on an agent as the influencing subject and the influenced object are disparate, the former is the inter-relationships between agents while the latter is the preference/choice of a single agent. Furthermore, the author considers combinatorial and collective decision-making and provides a framework model of influence across multiple agents and issues. In addition, this book: Addresses multiple sources of influence with various strengths and opposite polarities in group decision-making Provides both graphical and mathematical expressions of the three levels of influence Designs multiple weighted influences, opposite influences, and dominant influence rules.
Contents:
Introduction
Background
Social Influence Functions based on Social Choice
Matrix Influence Function based on Ordering Matrix
Graphical and Mathematical Expressions of the Three Levels of Influence
Addressing Coalitional and Structural Influence: A Probabilistic Approach
Multiple Sources of Influence across Agents and Issues
Multiple Weighted Influences
One Dominant Influence
Discussion, Conclusion, and Future Work.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-032-01352-6
9783032013521
OCLC:
1564842291

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