A policy iteration algorithm for nonzero-sum stochastic impulse games

Aïd, René; Bernal Martínez, Francisco Manuel; Mnif, Mohamed; Zabaljauregui, Diego; Zubelli, Jorge P.

Publication:
A policy iteration algorithm for nonzero-sum stochastic impulse games

dc.affiliation.dpto	UC3M. Departamento de Matemáticas	es
dc.contributor.author	Aïd, René
dc.contributor.author	Bernal Martínez, Francisco Manuel
dc.contributor.author	Mnif, Mohamed
dc.contributor.author	Zabaljauregui, Diego
dc.contributor.author	Zubelli, Jorge P.
dc.date.accessioned	2021-03-10T13:10:38Z
dc.date.available	2021-03-10T13:10:38Z
dc.date.issued	2019-02
dc.description	Research work conducted during the 22nd edition of CEMRACS, Numerical methods for stochastic models: control, uncertainty quantification, mean-field, July 17 - August 25, CIRM, Marseille	en
dc.description.abstract	This work presents a novel policy iteration algorithm to tackle nonzero-sum stochastic impulse games arising naturally in many applications. Despite the obvious impact of solving such problems, there are no suitable numerical methods available, to the best of our knowledge. Our method relies on the recently introduced characterisation of the value functions and Nash equilibrium via a system of quasi-variational inequalities. While our algorithm is heuristic and we do not provide a convergence analysis, numerical tests show that it performs convincingly in a wide range of situations, including the only analytically solvable example available in the literature at the time of writing.	en
dc.description.sponsorship	JPZ was supported by CNPq, FAPERJ, and the Brazilian-French network in Mathematics.FB gratefully acknowledges support from the Finance for Energy Market Research Centre (FiME).	en
dc.format.extent	19	es
dc.identifier.bibliographicCitation	ESAIM: Proceedings and Surveys, vol. 65, Feb. 2019 (CEMRACS 2017, Numerical methods for stochastic models: control, uncertainty quantification, mean-field, Marseille, France, July 17 - August 25, 2017) Pp. 27-45	en
dc.identifier.doi	https://doi.org/10.1051/proc/201965027
dc.identifier.issn	2267-3059
dc.identifier.publicationfirstpage	27	es
dc.identifier.publicationlastpage	45	es
dc.identifier.publicationtitle	ESAIM: Proceedings and Surveys: CEMRACS 2017, Numerical methods for stochastic models: control, uncertainty quantification, mean-field, Marseille, France, July 17 - August 25, 2017	en
dc.identifier.publicationvolume	65	es
dc.identifier.uri	https://hdl.handle.net/10016/32094
dc.identifier.uxxi	CC/0000031977
dc.language.iso	eng	en
dc.publisher	EDP Science	en
dc.relation.eventdate	2017-07-17	es
dc.relation.eventplace	Marsella, FRANCIA	es
dc.relation.eventtitle	CEMRACS 2017: Numerical methods for stochastic models: control, uncertainty quantification, mean-field	en
dc.rights	© EDP Sciences, SMAI 2019.	es
dc.rights	This is an Open Access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.	es
dc.rights	Atribución 3.0 España	*
dc.rights.accessRights	open access	en
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/es/	*
dc.subject.eciencia	Matemáticas	es
dc.subject.other	Stochastic impulse game	en
dc.subject.other	Nonzero-sum game	en
dc.subject.other	Nash equilibrium	en
dc.subject.other	Policy iteration	en
dc.subject.other	Howard's algorithm	en
dc.subject.other	Quasi-variational inequality	en
dc.title	A policy iteration algorithm for nonzero-sum stochastic impulse games	en
dc.type	conference paper	*
dc.type.hasVersion	VoR	*
dspace.entity.type	Publication