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The dollar auction with spiteful players

The dollar auction with spiteful players
The dollar auction with spiteful players
The dollar auction is an auction model used to analyse the dynamics of conflict escalation. In this paper, we analyse the course of an auction when participating players are spiteful, i.e., they are motivated not only by their own profit, but also by the desire to hurt the opponent. We investigate this model for the complete information setting, both for the standard scenario and for the situation where auction starts with nonzero bids. Our results give us insight into the possible effects of meanness onto conflict escalation.
2159-5399
AAAI Press
Waniek, Marcin
b0604cb4-d515-4e1f-8fd2-09a9cc420db4
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Michalak, Tomasz P.
18675d03-00c5-449c-9215-ba0f11d3302f
Jennings, Nicholas
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Waniek, Marcin
b0604cb4-d515-4e1f-8fd2-09a9cc420db4
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Michalak, Tomasz P.
18675d03-00c5-449c-9215-ba0f11d3302f
Jennings, Nicholas
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Waniek, Marcin, Tran-Thanh, Long, Michalak, Tomasz P. and Jennings, Nicholas (2017) The dollar auction with spiteful players. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence and the Twenty-Ninth Innovative Applications of Artificial Intelligence Conference. vol. 1, AAAI Press. 7 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

The dollar auction is an auction model used to analyse the dynamics of conflict escalation. In this paper, we analyse the course of an auction when participating players are spiteful, i.e., they are motivated not only by their own profit, but also by the desire to hurt the opponent. We investigate this model for the complete information setting, both for the standard scenario and for the situation where auction starts with nonzero bids. Our results give us insight into the possible effects of meanness onto conflict escalation.

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Accepted/In Press date: 12 September 2016
e-pub ahead of print date: 4 February 2017
Published date: 4 February 2017
Venue - Dates: Thirty-First AAAI Conference on Artificial Intelligence, , San Francisco, United States, 2017-02-04 - 2017-02-09
Organisations: Electronics & Computer Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 406360
URI: http://eprints.soton.ac.uk/id/eprint/406360
ISSN: 2159-5399
PURE UUID: c7de75ef-c7b0-481b-b39a-ecc6a33b1b35
ORCID for Long Tran-Thanh: ORCID iD orcid.org/0000-0003-1617-8316

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Date deposited: 10 Mar 2017 10:45
Last modified: 15 Mar 2024 12:19

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Contributors

Author: Marcin Waniek
Author: Long Tran-Thanh ORCID iD
Author: Tomasz P. Michalak
Author: Nicholas Jennings

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