Standard

MFGs for Finite-State Models. / Kolokoltsov, Vassili N.; Malafeyev, Oleg A.

Springer Series in Operations Research and Financial Engineering. Springer Nature, 2019. стр. 111-118 (Springer Series in Operations Research and Financial Engineering).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › глава/раздел › научная › Рецензирование

Harvard

Kolokoltsov, VN & Malafeyev, OA 2019, MFGs for Finite-State Models. в Springer Series in Operations Research and Financial Engineering. Springer Series in Operations Research and Financial Engineering, Springer Nature, стр. 111-118. https://doi.org/10.1007/978-3-030-12371-0_5

APA

Kolokoltsov, V. N., & Malafeyev, O. A. (2019). MFGs for Finite-State Models. в Springer Series in Operations Research and Financial Engineering (стр. 111-118). (Springer Series in Operations Research and Financial Engineering). Springer Nature. https://doi.org/10.1007/978-3-030-12371-0_5

Vancouver

Kolokoltsov VN, Malafeyev OA. MFGs for Finite-State Models. в Springer Series in Operations Research and Financial Engineering. Springer Nature. 2019. стр. 111-118. (Springer Series in Operations Research and Financial Engineering). https://doi.org/10.1007/978-3-030-12371-0_5

Author

Kolokoltsov, Vassili N. ; Malafeyev, Oleg A. / MFGs for Finite-State Models. Springer Series in Operations Research and Financial Engineering. Springer Nature, 2019. стр. 111-118 (Springer Series in Operations Research and Financial Engineering).

BibTeX

@inbook{48fafc620aa4459ab54d533bc41c72c2,
title = "MFGs for Finite-State Models",
abstract = "In this chapter, we introduce the MFG framework for discrete state spaces, stressing the points that are most relevant for the models studied in the next chapters. As was already mentioned, the difference between the present MFG setting and the modeling of Part I is that now the small agents themselves become rational optimizers and are not supposed just to follow some prescribed deterministic or stochastic strategies (such as myopic behavior). For simplicity, in treating MFG we will exclusively use finite-state models and will not touch the extensions to countable state spaces, though the results of Chapter 4 allow one to extend large portions of the theory more or less directly to this more general framework.",
author = "Kolokoltsov, {Vassili N.} and Malafeyev, {Oleg A.}",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2019",
doi = "10.1007/978-3-030-12371-0_5",
language = "English",
series = "Springer Series in Operations Research and Financial Engineering",
publisher = "Springer Nature",
pages = "111--118",
booktitle = "Springer Series in Operations Research and Financial Engineering",
address = "Germany",

}

RIS

TY - CHAP

T1 - MFGs for Finite-State Models

AU - Kolokoltsov, Vassili N.

AU - Malafeyev, Oleg A.

N1 - Publisher Copyright: © 2019, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2019

Y1 - 2019

N2 - In this chapter, we introduce the MFG framework for discrete state spaces, stressing the points that are most relevant for the models studied in the next chapters. As was already mentioned, the difference between the present MFG setting and the modeling of Part I is that now the small agents themselves become rational optimizers and are not supposed just to follow some prescribed deterministic or stochastic strategies (such as myopic behavior). For simplicity, in treating MFG we will exclusively use finite-state models and will not touch the extensions to countable state spaces, though the results of Chapter 4 allow one to extend large portions of the theory more or less directly to this more general framework.

AB - In this chapter, we introduce the MFG framework for discrete state spaces, stressing the points that are most relevant for the models studied in the next chapters. As was already mentioned, the difference between the present MFG setting and the modeling of Part I is that now the small agents themselves become rational optimizers and are not supposed just to follow some prescribed deterministic or stochastic strategies (such as myopic behavior). For simplicity, in treating MFG we will exclusively use finite-state models and will not touch the extensions to countable state spaces, though the results of Chapter 4 allow one to extend large portions of the theory more or less directly to this more general framework.

UR - http://www.scopus.com/inward/record.url?scp=85098065403&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-12371-0_5

DO - 10.1007/978-3-030-12371-0_5

M3 - Chapter

AN - SCOPUS:85098065403

T3 - Springer Series in Operations Research and Financial Engineering

SP - 111

EP - 118

BT - Springer Series in Operations Research and Financial Engineering

PB - Springer Nature

ER -

ID: 72679196