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Reaching a Consensus

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TLDR
In this article, the authors consider a group of individuals who must act together as a team or committee, and assume that each individual in the group has his own subjective probability distribution for the unknown value of some parameter.
Abstract
Consider a group of individuals who must act together as a team or committee, and suppose that each individual in the group has his own subjective probability distribution for the unknown value of some parameter. A model is presented which describes how the group might reach agreement on a common subjective probability distribution for the parameter by pooling their individual opinions. The process leading to the consensus is explicitly described and the common distribution that is reached is explicitly determined. The model can also be applied to problems of reaching a consensus when the opinion of each member of the group is represented simply as a point estimate of the parameter rather than as a probability distribution.

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Citations
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Journal ArticleDOI

The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

Consensus and Cooperation in Networked Multi-Agent Systems

TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Journal ArticleDOI

Stability of multiagent systems with time-dependent communication links

TL;DR: It is observed that more communication does not necessarily lead to faster convergence and may eventually even lead to a loss of convergence, even for the simple models discussed in the present paper.
Posted Content

Opinion dynamics and bounded confidence models, analysis and simulation

TL;DR: This article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations for the classical model of consensus formation, a time-dependent version and a nonlinear version with bounded confidence of the agents.
Journal ArticleDOI

Combining forecasts: A review and annotated bibliography

TL;DR: In this article, the authors provide a review and annotated bibliography of that literature, including contributions from the forecasting, psychology, statistics, and management science literatures, providing a guide to the literature for students and researchers and to help researchers locate contributions in specific areas, both theoretical and applied.
References
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Book

Assessment and evaluation of subjective probability distributions

TL;DR: In this paper, a person faced with a problem of decision under uncertainty should proceed to find a course of action which is consistent with his judgement and preferences, i.e., he judges the uncertainty of future outcomes and quantifies his beliefs in probabilities.

Externally bayesian groups

TL;DR: In this article, an axiom of group rationality is introduced, namely, that to an outsider the decisions of the group appear like the decision of a Bayesian, and its implications are explored when the group decision-making procedure either can or cannot be amended.
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