Standard

Equilibrium and cooperation in repeated hierarchical games. / Petrosyan, Leon; Pankratova, Yaroslavna.

Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. ed. / Michael Khachay; Panos Pardalos; Yury Kochetov. Springer Nature, 2019. p. 685-696 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11548 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Petrosyan, L & Pankratova, Y 2019, Equilibrium and cooperation in repeated hierarchical games. in M Khachay, P Pardalos & Y Kochetov (eds), Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11548 LNCS, Springer Nature, pp. 685-696, 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019, Ekaterinburg, Russian Federation, 8/07/19. https://doi.org/10.1007/978-3-030-22629-9_48

APA

Petrosyan, L., & Pankratova, Y. (2019). Equilibrium and cooperation in repeated hierarchical games. In M. Khachay, P. Pardalos, & Y. Kochetov (Eds.), Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings (pp. 685-696). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11548 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-22629-9_48

Vancouver

Petrosyan L, Pankratova Y. Equilibrium and cooperation in repeated hierarchical games. In Khachay M, Pardalos P, Kochetov Y, editors, Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. Springer Nature. 2019. p. 685-696. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-22629-9_48

Author

Petrosyan, Leon ; Pankratova, Yaroslavna. / Equilibrium and cooperation in repeated hierarchical games. Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. editor / Michael Khachay ; Panos Pardalos ; Yury Kochetov. Springer Nature, 2019. pp. 685-696 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{cbcf343282b1418ebe685ec79bc11238,
title = "Equilibrium and cooperation in repeated hierarchical games",
abstract = "In the paper a two-level infinitely repeated hierarchical game with one player (center) C0 on the first level and S1...Sn subordinate players on the second is considered. On each stage of the game player C0 selects vector x=(x1....xn) from a given set X, in which each component represents vector of resources delivered by C0 to one of subordinate players, i.e. (formula presented). At the second level, Si i=1,2..,n, choose the controls (formula presented), where Yi(xi) depends upon the choice of player C0. In this game, a set of different Nash equilibrium also based on threat and punishment strategies is obtained. In one case, the center enforces special behavior of subordinate firms (vector of manufactured goods), threatening to deprive them of resources on the next steps if the subordinate firms refuse to implement the prescribed behavior. In another case, the subordinate firms can force the center to use a certain resource allocation threatening to stop production. Using different combinations of such behaviors on different stages of the game, we obtain a wide class of Nash equilibrium in the game under consideration. The cooperative version of the game is also considered. The conditions are derived under which the cooperative behavior can be supported by Nash Equilibrium or Strong Nash Equilibrium (Nash Equilibrium stable against deviations of coalitions).",
keywords = "Cooperation, Nash equilibrium, Repeated hierarchical game",
author = "Leon Petrosyan and Yaroslavna Pankratova",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-22629-9_48",
language = "English",
isbn = "9783030226282",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "685--696",
editor = "Michael Khachay and Panos Pardalos and Yury Kochetov",
booktitle = "Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings",
address = "Germany",
note = "18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019 ; Conference date: 08-07-2019 Through 12-07-2019",

}

RIS

TY - GEN

T1 - Equilibrium and cooperation in repeated hierarchical games

AU - Petrosyan, Leon

AU - Pankratova, Yaroslavna

PY - 2019/1/1

Y1 - 2019/1/1

N2 - In the paper a two-level infinitely repeated hierarchical game with one player (center) C0 on the first level and S1...Sn subordinate players on the second is considered. On each stage of the game player C0 selects vector x=(x1....xn) from a given set X, in which each component represents vector of resources delivered by C0 to one of subordinate players, i.e. (formula presented). At the second level, Si i=1,2..,n, choose the controls (formula presented), where Yi(xi) depends upon the choice of player C0. In this game, a set of different Nash equilibrium also based on threat and punishment strategies is obtained. In one case, the center enforces special behavior of subordinate firms (vector of manufactured goods), threatening to deprive them of resources on the next steps if the subordinate firms refuse to implement the prescribed behavior. In another case, the subordinate firms can force the center to use a certain resource allocation threatening to stop production. Using different combinations of such behaviors on different stages of the game, we obtain a wide class of Nash equilibrium in the game under consideration. The cooperative version of the game is also considered. The conditions are derived under which the cooperative behavior can be supported by Nash Equilibrium or Strong Nash Equilibrium (Nash Equilibrium stable against deviations of coalitions).

AB - In the paper a two-level infinitely repeated hierarchical game with one player (center) C0 on the first level and S1...Sn subordinate players on the second is considered. On each stage of the game player C0 selects vector x=(x1....xn) from a given set X, in which each component represents vector of resources delivered by C0 to one of subordinate players, i.e. (formula presented). At the second level, Si i=1,2..,n, choose the controls (formula presented), where Yi(xi) depends upon the choice of player C0. In this game, a set of different Nash equilibrium also based on threat and punishment strategies is obtained. In one case, the center enforces special behavior of subordinate firms (vector of manufactured goods), threatening to deprive them of resources on the next steps if the subordinate firms refuse to implement the prescribed behavior. In another case, the subordinate firms can force the center to use a certain resource allocation threatening to stop production. Using different combinations of such behaviors on different stages of the game, we obtain a wide class of Nash equilibrium in the game under consideration. The cooperative version of the game is also considered. The conditions are derived under which the cooperative behavior can be supported by Nash Equilibrium or Strong Nash Equilibrium (Nash Equilibrium stable against deviations of coalitions).

KW - Cooperation

KW - Nash equilibrium

KW - Repeated hierarchical game

UR - http://www.scopus.com/inward/record.url?scp=85067671871&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/equilibrium-cooperation-repeated-hierarchical-games

U2 - 10.1007/978-3-030-22629-9_48

DO - 10.1007/978-3-030-22629-9_48

M3 - Conference contribution

AN - SCOPUS:85067671871

SN - 9783030226282

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 685

EP - 696

BT - Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings

A2 - Khachay, Michael

A2 - Pardalos, Panos

A2 - Kochetov, Yury

PB - Springer Nature

T2 - 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019

Y2 - 8 July 2019 through 12 July 2019

ER -

ID: 43716266