Group formation on a small-world: experiment and modelling

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Group formation on a small-world : experiment and modelling. / Bhattacharya, Kunal; Takko, Tuomas; Monsivais, Daniel; Kaski, Kimmo.

julkaisussa: Journal of the Royal Society Interface, Vuosikerta 16, Nro 156, 26.07.2019.

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

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Bibtex - Lataa

@article{da333e07cd724064bfdeb16e0d5dfd9b,
title = "Group formation on a small-world: experiment and modelling",
abstract = "As a step towards studying human-agent collectives, we conduct an online game with human participants cooperating on a network. The game is presented in the context of achieving group formation through local coordination. The players set initially to a small-world network with limited information on the location of other players, coordinate their movements to arrange themselves into groups. To understand the decision-making process, we construct a data-driven model of agents based on probability matching. The model allows us to gather insight into the nature and degree of rationality employed by the human players. By varying the parameters in agent-based simulations, we are able to benchmark the human behaviour. We observe that while the players use the neighbourhood information in limited capacity, the perception of risk is optimal. We also find that for certain parameter ranges, the agents are able to act more efficiently when compared to the human players. This approach would allow us to simulate the collective dynamics in games with agents having varying strategies playing alongside human proxies.",
keywords = "collective intelligence, complex networks, coordination game",
author = "Kunal Bhattacharya and Tuomas Takko and Daniel Monsivais and Kimmo Kaski",
year = "2019",
month = "7",
day = "26",
doi = "10.1098/rsif.2018.0814",
language = "English",
volume = "16",
journal = "Journal of the Royal Society Interface",
issn = "1742-5689",
publisher = "Royal Society of London",
number = "156",

}

RIS - Lataa

TY - JOUR

T1 - Group formation on a small-world

T2 - experiment and modelling

AU - Bhattacharya, Kunal

AU - Takko, Tuomas

AU - Monsivais, Daniel

AU - Kaski, Kimmo

PY - 2019/7/26

Y1 - 2019/7/26

N2 - As a step towards studying human-agent collectives, we conduct an online game with human participants cooperating on a network. The game is presented in the context of achieving group formation through local coordination. The players set initially to a small-world network with limited information on the location of other players, coordinate their movements to arrange themselves into groups. To understand the decision-making process, we construct a data-driven model of agents based on probability matching. The model allows us to gather insight into the nature and degree of rationality employed by the human players. By varying the parameters in agent-based simulations, we are able to benchmark the human behaviour. We observe that while the players use the neighbourhood information in limited capacity, the perception of risk is optimal. We also find that for certain parameter ranges, the agents are able to act more efficiently when compared to the human players. This approach would allow us to simulate the collective dynamics in games with agents having varying strategies playing alongside human proxies.

AB - As a step towards studying human-agent collectives, we conduct an online game with human participants cooperating on a network. The game is presented in the context of achieving group formation through local coordination. The players set initially to a small-world network with limited information on the location of other players, coordinate their movements to arrange themselves into groups. To understand the decision-making process, we construct a data-driven model of agents based on probability matching. The model allows us to gather insight into the nature and degree of rationality employed by the human players. By varying the parameters in agent-based simulations, we are able to benchmark the human behaviour. We observe that while the players use the neighbourhood information in limited capacity, the perception of risk is optimal. We also find that for certain parameter ranges, the agents are able to act more efficiently when compared to the human players. This approach would allow us to simulate the collective dynamics in games with agents having varying strategies playing alongside human proxies.

KW - collective intelligence

KW - complex networks

KW - coordination game

UR - http://www.scopus.com/inward/record.url?scp=85069320824&partnerID=8YFLogxK

U2 - 10.1098/rsif.2018.0814

DO - 10.1098/rsif.2018.0814

M3 - Article

VL - 16

JO - Journal of the Royal Society Interface

JF - Journal of the Royal Society Interface

SN - 1742-5689

IS - 156

ER -

ID: 35680110