Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bowling alone: the collapse and revival of American community
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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Autonomous Agents and Multi-Agent Systems
Game Theory and Operations Research: Some Musings 50 Years Later
Operations Research
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Organization Science
Algorithmic Game Theory
Social and Economic Networks
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Theory of Conditional Games
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This paper describes how a nascent collective of individuals can coalesce into a complex social system. The systematic study of such scenarios requires a mathematical framework within which to model the behavior of the individual members of the collective. As individuals interact, they develop social relationships and exchange resources --- that is, they develop social capital that quantifies the value of social influence that individuals exert on each other. Social capital can be expressed via conditional preference orderings for each individual. Conditional preferences reflect the influence relationships of an interacting social collective. Conditional preference orderings can then be aggregated via conditional game theory to form a concordant utility that provides an emergent group-level ordering of the harmony of interests of the members of the collective. We can thus develop a complete social model that takes into consideration all social relationships as they propagate through the system. Solution concepts can then be defined that simultaneously account for both group-level and individual-level interests.