scholarly journals On the Belief Merging by Negotiation

2014 ◽  
Vol 35 ◽  
pp. 147-155 ◽  
Author(s):  
Trong Hieu Tran ◽  
Quoc Bao Vo ◽  
Thi Hong Khanh Nguyen
Keyword(s):  
Belief Merging

Merginator: A belief merging tool for consensus support

2018 ◽  
Vol 34 (5) ◽  
pp. 3199-3210 ◽  
Author(s):  
Pilar Pozos-Parra ◽  
Oscar Chávez-Bosquez ◽  
Kevin McAreavey
Keyword(s):  
Belief Merging

Truth approximation, belief merging, and peer disagreement

Synthese ◽  
2014 ◽  
Vol 191 (11) ◽  
pp. 2383-2401 ◽  
Author(s):  
Gustavo Cevolani
Keyword(s):  
Truth Approximation ◽  
Peer Disagreement ◽  
Belief Merging

scholarly journals Belief Merging Operators as Maximum Likelihood Estimators

2020 ◽  
Author(s):  
Patricia Everaere ◽  
Sebastien Konieczny ◽  
Pierre Marquis
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimators ◽  
Noise Model ◽  
Belief Merging ◽  
The World ◽  
Natural Noise ◽  
True State ◽  
Merging Process ◽  
Rationality Postulates ◽  
Noise Models

We study how belief merging operators can be considered as maximum likelihood estimators, i.e., we assume that there exists a (unknown) true state of the world and that each agent participating in the merging process receives a noisy signal of it, characterized by a noise model. The objective is then to aggregate the agents' belief bases to make the best possible guess about the true state of the world. In this paper, some logical connections between the rationality postulates for belief merging (IC postulates) and simple conditions over the noise model under consideration are exhibited. These results provide a new justification for IC merging postulates. We also provide results for two specific natural noise models: the world swap noise and the atom swap noise, by identifying distance-based merging operators that are maximum likelihood estimators for these two noise models.

scholarly journals Conciliation through Iterated Belief Merging

2007 ◽  
Vol 17 (5) ◽  
pp. 909-937 ◽  
Author(s):  
O. Gauwin ◽  
S. Konieczny ◽  
P. Marquis
Keyword(s):  
Belief Merging

scholarly journals Belief Merging and Judgment Aggregation in Fuzzy Setting

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Ismat Beg ◽  
Nabeel Butt
Keyword(s):  
Fuzzy Logic ◽  
Social Choice ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Judgment Aggregation ◽  
Belief Merging ◽  
Aggregation Functions ◽  
Fuzzy Aggregation ◽  
Doctrinal Paradox ◽  
Fuzzy Setting

We explore how judgment aggregation and belief merging in the framework of fuzzy logic can help resolve the “Doctrinal Paradox.” We also illustrate the use of fuzzy aggregation functions in social choice theory.

Social choice theory, belief merging, and strategy-proofness

2006 ◽  
Vol 7 (1) ◽  
pp. 61-79 ◽  
Author(s):  
Samir Chopra ◽  
Aditya Ghose ◽  
Thomas Meyer
Keyword(s):  
Social Choice ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Belief Merging ◽  
Strategy Proofness

scholarly journals Proportional Belief Merging

2020 ◽  
Vol 34 (03) ◽  
pp. 2822-2829 ◽  
Author(s):  
Adrian Haret ◽  
Martin Lackner ◽  
Andreas Pfandler ◽  
Johannes P. Wallner
Keyword(s):  
Social Choice ◽  
Complexity Analysis ◽  
The Other ◽  
Belief Merging ◽  
Rationality Postulates

In this paper we introduce proportionality to belief merging. Belief merging is a framework for aggregating information presented in the form of propositional formulas, and it generalizes many aggregation models in social choice. In our analysis, two incompatible notions of proportionality emerge: one similar to standard notions of proportionality in social choice, the other more in tune with the logic-based merging setting. Since established merging operators meet neither of these proportionality requirements, we design new proportional belief merging operators. We analyze the proposed operators against established rationality postulates, finding that current approaches to proportionality from the field of social choice are, at their core, incompatible with standard rationality postulates in belief merging. We provide characterization results that explain the underlying conflict, and provide a complexity analysis of our novel operators.

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