Paper Info
Title
Exploiting Vagueness for Multi-agent Consensus
Abstract
A framework for consensus modelling is introduced using Kleene's three valued logic as a means to express vagueness in agents' beliefs. Explicitly borderline cases are inherent to propositions involving vague concepts where sentences of a propositional language may be absolutely true, absolutely false or borderline. By exploiting these intermediate truth values, we can allow agents to adopt amore vague interpretation of underlying concepts in order to weaken their beliefs and reduce the levels of inconsistency, so as to achieve consensus. We consider a consensus combination operation which results in agents adopting the borderline truth value as a shared viewpoint if they are in direct conflict. Simulation experiments are presented which show that applying this operator to agents chosen at random (subject to a consistency threshold) from a population, with initially diverse opinions, results in convergence to a smaller set of more precise shared beliefs. Furthermore, if the choice of agents for combination is dependent on the payoff of their beliefs, this acting as a proxy for performance or usefulness, then the system converges to beliefs which, on average, have higher payoff.
Year
DOI
Venue
2016
10.1007/978-981-10-2564-8_5
Studies in Computational Intelligence
Keywords
Field
DocType
Agent-based modelling,Many-valued logics,Belief aggregation,Consensus
Convergence (routing),Population,Vagueness,Three-valued logic,Truth value,Artificial intelligence,Operator (computer programming),Mathematics,Stochastic game
Journal
Volume
ISSN
Citations 
670
1860-949X
2
PageRank 
References 
Authors
0.53
6
2
Name
Order
Citations
PageRank
Michael Crosscombe142.60
Jonathan Lawry217219.06