The University of Southampton
University of Southampton Institutional Repository

Last round convergence and no-dynamic regret in asymmetric repeated games

Last round convergence and no-dynamic regret in asymmetric repeated games
Last round convergence and no-dynamic regret in asymmetric repeated games
This paper considers repeated games in which one player has a different objective than others. In particular, we investigate repeated two-player zero-sum games where the column player not only aims to minimize her regret but also stabilize the actions. Suppose that while repeatedly playing this game, the row player chooses her strategy at each round by using a no-regret algorithm to minimize her regret. We develop a no-dynamic regret algorithm for the column player to exhibit last round convergence to a minimax equilibrium. We show that our algorithm is efficient against a large set of popular no-regret algorithms the row player can use, including the multiplicative weights update algorithm, general follow-the-regularized-leader and any no-regret algorithms satisfy a property so called “stability”.
553-577
PMLR
Dinh, Le Cong
e89b4443-9eff-4790-b101-9eabe5ef947c
Nguyen, Tri-Dung
a6aa7081-6bf7-488a-b72f-510328958a8e
Zemhoho, Alain B.
2ae46009-ed9e-4d2a-a08b-d6df91d9a211
Tran-Thanh, Long
633282bf-f7ff-4137-ada6-6d4f19262676
Feldman, Vitaly
Ligett, Katrina
Sabato, Sivan
Dinh, Le Cong
e89b4443-9eff-4790-b101-9eabe5ef947c
Nguyen, Tri-Dung
a6aa7081-6bf7-488a-b72f-510328958a8e
Zemhoho, Alain B.
2ae46009-ed9e-4d2a-a08b-d6df91d9a211
Tran-Thanh, Long
633282bf-f7ff-4137-ada6-6d4f19262676
Feldman, Vitaly
Ligett, Katrina
Sabato, Sivan

Dinh, Le Cong, Nguyen, Tri-Dung, Zemhoho, Alain B. and Tran-Thanh, Long (2021) Last round convergence and no-dynamic regret in asymmetric repeated games. Feldman, Vitaly, Ligett, Katrina and Sabato, Sivan (eds.) In Proceedings of the 32nd International Conference on Algorithmic Learning Theory. vol. 132, PMLR. pp. 553-577 .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper considers repeated games in which one player has a different objective than others. In particular, we investigate repeated two-player zero-sum games where the column player not only aims to minimize her regret but also stabilize the actions. Suppose that while repeatedly playing this game, the row player chooses her strategy at each round by using a no-regret algorithm to minimize her regret. We develop a no-dynamic regret algorithm for the column player to exhibit last round convergence to a minimax equilibrium. We show that our algorithm is efficient against a large set of popular no-regret algorithms the row player can use, including the multiplicative weights update algorithm, general follow-the-regularized-leader and any no-regret algorithms satisfy a property so called “stability”.

Text
dinh21a - Accepted Manuscript
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 21 December 2020
e-pub ahead of print date: 1 April 2021

Identifiers

Local EPrints ID: 448061
URI: http://eprints.soton.ac.uk/id/eprint/448061
PURE UUID: 46435bc8-66f5-43df-a6b5-0802bbf3fda3
ORCID for Tri-Dung Nguyen: ORCID iD orcid.org/0000-0002-4158-9099

Catalogue record

Date deposited: 01 Apr 2021 15:41
Last modified: 13 Apr 2021 01:45

Export record

Contributors

Author: Le Cong Dinh
Author: Tri-Dung Nguyen ORCID iD
Author: Alain B. Zemhoho
Author: Long Tran-Thanh
Editor: Vitaly Feldman
Editor: Katrina Ligett
Editor: Sivan Sabato

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×