The University of Southampton
University of Southampton Institutional Repository

Fostering cooperation in structured populations through local and global interference strategies

Fostering cooperation in structured populations through local and global interference strategies
Fostering cooperation in structured populations through local and global interference strategies

We study the situation of an exogenous decision-maker aiming to encourage a population of autonomous, self-regarding agents to follow a desired behaviour at a minimal cost. The primary goal is therefore to reach an efficient trade-off between pushing the agents to achieve the desired configuration while minimising the total investment. To this end, we test several interference paradigms resorting to simulations of agents facing a cooperative dilemma in a spatial arrangement. We systematically analyse and compare interference strategies rewarding local or global behavioural patterns. Our results show that taking into account the neighbourhood's local properties, such as its level of cooperativeness, can lead to a significant improvement regarding cost efficiency while guaranteeing high levels of cooperation. As such, we argue that local interference strategies are more efficient than global ones in fostering cooperation in a population of autonomous agents.

289-295
International Joint Conferences on Artificial Intelligence
Han, The Anh
b80447eb-91f3-449b-bfce-e5a6af0447d9
Lynch, Simon
5dc7147f-9d0b-4043-ab09-00e3c5179219
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Santos, Francisco C.
a509c59e-1995-44e5-8dca-500a37a50dc1
Han, The Anh
b80447eb-91f3-449b-bfce-e5a6af0447d9
Lynch, Simon
5dc7147f-9d0b-4043-ab09-00e3c5179219
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Santos, Francisco C.
a509c59e-1995-44e5-8dca-500a37a50dc1

Han, The Anh, Lynch, Simon, Tran-Thanh, Long and Santos, Francisco C. (2018) Fostering cooperation in structured populations through local and global interference strategies. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. vol. 2018-July, International Joint Conferences on Artificial Intelligence. pp. 289-295 .

Record type: Conference or Workshop Item (Paper)

Abstract

We study the situation of an exogenous decision-maker aiming to encourage a population of autonomous, self-regarding agents to follow a desired behaviour at a minimal cost. The primary goal is therefore to reach an efficient trade-off between pushing the agents to achieve the desired configuration while minimising the total investment. To this end, we test several interference paradigms resorting to simulations of agents facing a cooperative dilemma in a spatial arrangement. We systematically analyse and compare interference strategies rewarding local or global behavioural patterns. Our results show that taking into account the neighbourhood's local properties, such as its level of cooperativeness, can lead to a significant improvement regarding cost efficiency while guaranteeing high levels of cooperation. As such, we argue that local interference strategies are more efficient than global ones in fostering cooperation in a population of autonomous agents.

Full text not available from this repository.

More information

Published date: 2018
Venue - Dates: 27th International Joint Conference on Artificial Intelligence, Stockholm, Sweden, 2018-07-13 - 2018-07-19

Identifiers

Local EPrints ID: 426266
URI: https://eprints.soton.ac.uk/id/eprint/426266
PURE UUID: ac03bec0-7fe8-48b0-b90e-8fcff1dd4139
ORCID for Long Tran-Thanh: ORCID iD orcid.org/0000-0003-1617-8316

Catalogue record

Date deposited: 21 Nov 2018 17:30
Last modified: 03 Dec 2019 01:42

Export record

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 https://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.

×