RaBVItG V1.0: Radial Basis Value
Iteration Game Algorithm
What is RaBVItG?
RaBVItG is an algorithm which aim to approximate feedback-Nash equilibria for
deterministic differential games. It is based on value iteration schemes in a meshfree context. It is used to approximate optimal
feedback Nash policies for multi-players, trying to tackle the dimensionality
that involves, in general, this type of problems. Moreover, RaBVItG
also implements a game iteration structure that computes the game equilibrium
at every value iteration step, in order to increase the accuracy of the
solutions.
How to run the model?
Requirements: Matlab (tested with 2018b or later)
Launch Matlab
Choose one example.
Run ‘MAIN.m’
to perform a simulation
Contact for additional support: joherrer@est-econ.uc3m.es or ivorra@mat.ucm.es
Download (Version 3.0 – Date: 15/10/2018):
License:
This
software is for personal use and reserved to public research or educational
purposes. Any professional utilization is forbidden without the authors'
agreement.
For
any additional information, please contact:
joherrer@est-econ.uc3m.es or ivorra@mat.ucm.es
Some reference articles:
If you use this software during a research
work, you could use the following references about the validation and the
description of the method:
1. Jorge
Herrera, Benjamin Ivorra and Ángel M. Ramos
RaBVItG: An Algorithm for Solving a Class of Multi-Players Feedback Nash
Differential Games
May 2019 Mathematical Problems in Engineering
2019(Article ID 1417275):14
DOI: 10.1155/2019/1417275
Workgroup:
Jorge Herrera de la Cruz (A), Benjamin Ivorra (B), and Ángel Manuel Ramos
(B)
(A) Department of Economic Analysis and Quantitative
Economics, Complutense University of Madrid, Campus
de Somosaguas, s/n, 28223 Pozuelo
de Alarcón, Spain
(B) MOMAT research group, IMI-Institute & Applied
Mathematics Department. Complutense University of Madrid,
Spain.