Equilibria and learning dynamics in mixed network coordination/anti-coordination games
(2021) 2021 60th IEEE Conference on Decision and Control (CDC) p.4982-4987- Abstract
- Whilst network coordination games and network anti-coordination games have received a considerable amount of attention in the literature, network games with coexisting coordinating and anti-coordinating players are known to exhibit more complex behaviors. In fact, depending on the network structure, such games may even fail to have pure-strategy Nash equilibria. An example is represented by the well-known matching pennies (discoordination) game.In this work, we first provide graph-theoretic conditions for the existence of pure-strategy Nash equilibria in mixed network coordination/anti-coordination games of arbitrary size. For the case where such conditions are met, we then study the asymptotic behavior of best-response dynamics and... (More)
- Whilst network coordination games and network anti-coordination games have received a considerable amount of attention in the literature, network games with coexisting coordinating and anti-coordinating players are known to exhibit more complex behaviors. In fact, depending on the network structure, such games may even fail to have pure-strategy Nash equilibria. An example is represented by the well-known matching pennies (discoordination) game.In this work, we first provide graph-theoretic conditions for the existence of pure-strategy Nash equilibria in mixed network coordination/anti-coordination games of arbitrary size. For the case where such conditions are met, we then study the asymptotic behavior of best-response dynamics and provide sufficient conditions for finite-time convergence to the set of Nash equilibria. Our results build on an extension and refinement of the notion of network cohesiveness and on the formulation of the new concept of network indecomposibility. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/854188ac-118a-4826-bc13-0ebeaa9c05ff
- author
- Arditti, Laura ; Como, Giacomo LU ; Fagnani, Fabio and Vanelli, Martina
- organization
- publishing date
- 2021-12-14
- type
- Contribution to conference
- publication status
- published
- subject
- pages
- 4982 - 4987
- conference name
- 2021 60th IEEE Conference on Decision and Control (CDC)
- conference dates
- 2021-12-14 - 2021-12-17
- external identifiers
-
- scopus:85116794066
- DOI
- 10.1109/CDC45484.2021.9683414
- project
- Dynamics of Complex Socio-Technological Network Systems
- language
- English
- LU publication?
- yes
- id
- 854188ac-118a-4826-bc13-0ebeaa9c05ff
- alternative location
- https://ieeexplore.ieee.org/document/9683414/
- date added to LUP
- 2022-02-14 17:31:00
- date last changed
- 2022-05-04 23:41:22
@misc{854188ac-118a-4826-bc13-0ebeaa9c05ff,
abstract = {{Whilst network coordination games and network anti-coordination games have received a considerable amount of attention in the literature, network games with coexisting coordinating and anti-coordinating players are known to exhibit more complex behaviors. In fact, depending on the network structure, such games may even fail to have pure-strategy Nash equilibria. An example is represented by the well-known matching pennies (discoordination) game.In this work, we first provide graph-theoretic conditions for the existence of pure-strategy Nash equilibria in mixed network coordination/anti-coordination games of arbitrary size. For the case where such conditions are met, we then study the asymptotic behavior of best-response dynamics and provide sufficient conditions for finite-time convergence to the set of Nash equilibria. Our results build on an extension and refinement of the notion of network cohesiveness and on the formulation of the new concept of network indecomposibility.}},
author = {{Arditti, Laura and Como, Giacomo and Fagnani, Fabio and Vanelli, Martina}},
language = {{eng}},
month = {{12}},
pages = {{4982--4987}},
title = {{Equilibria and learning dynamics in mixed network coordination/anti-coordination games}},
url = {{http://dx.doi.org/10.1109/CDC45484.2021.9683414}},
doi = {{10.1109/CDC45484.2021.9683414}},
year = {{2021}},
}