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Bruce Foltz, Michael Craig Rhodes, Fabien Schang, Sergey S. Tarasenko, George Kiraz, Andrew Schumann,

Independent researcher. Holds PhD in Informatics from Kyoto University (Kyoto, Japan).
The main research interests include artificial neural networks and brain modeling,
reflexivity related research and Reflexive Game Theory (RGT). Main research results are 
experimental discovery of Golden ratio in human guessing performance (Blind Choice),
solution of inverse task of RGT and concept of emotional Reflexive Games,
general framework for development of the cortex-like visual object recognition system.


Modeling Multistage Decision Processes with Reflexive Game Theory

Reflexive Game Theory (RGT) has been designed to model a single session of decision making in a group. On the other hand, often one final decision is a result of series of discussions, which are dedicated to various aspects of the final decision. This paper introduces approach to model such multi-stage decision making processes by means of RGT. The basic idea is to set particular parameters (group structure, mutual relationships and influencess, etc.) during the series of decision making sessions.  To illustrate this idea three examples are provided.


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