%0 Journal Article
%T Game Theory Based Model for Predictive Analytics Using Distributed Position Function
%A Mirhossein Mousavi Karimi
%A Shahram Rahimi
%J International Journal of Intelligence Science
%P 22-47
%@ 2163-0356
%D 2024
%I Scientific Research Publishing
%R 10.4236/ijis.2024.141002
%X This paper presents a game theory-based method for predicting the
outcomes of negotiation and group decision-making problems. We propose an
extension to the BDM model to address problems where actors¡¯ positions are
distributed over a position spectrum. We generalize the concept of position in
the model to incorporate continuous positions for the actors, enabling them to
have more flexibility in defining their targets. We explore different possible
functions to study the role of the position function and discuss appropriate distance measures for computing
the distance between the positions of actors. To validate the proposed extension, we demonstrate
the trustworthiness of our model¡¯s performance and interpretation by
replicating the results based on data used in earlier studies.
%K Distributed Position Function
%K Game Theory
%K Group Decision Making
%K Predictive Analytics
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=130292