Righi, S;
Takács, K;
(2014)
Degree variance and emotional strategies catalyze cooperation in dynamic signed networks.
In:
Proceedings of the 28th European Conference on Modelling and Simulation ECMS 2014.
(pp. pp. 738-744).
ECMS:European Council for Modelling and Simulation: Brescia, Italy.
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Abstract
We study the problem of the emergence of cooperation in dynamic signed networks where agent strategies coevolve with relational signs and network topology. Running simulations based on an agent-based model, we compare results obtained in a regular lattice initialization with those obtained on a comparable random network initialization. We show that the increased degree heterogeneity at the outset enlarges the parametric conditions in which cooperation survives in the long run. Furthermore, we show how the presence of sign-dependent emotional strategies catalyze the evolution of cooperation with both network topology initializations. Proceedings 28th European Conference on Modelling and Simulation © ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors).
Type: | Proceedings paper |
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Title: | Degree variance and emotional strategies catalyze cooperation in dynamic signed networks |
Event: | 28th European Conference on Modelling and Simulation ECMS 2014 |
ISBN-13: | 9780956494481 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | http://www.scs-europe.net/conf/ecms2014/ecms2014pr... |
Language: | English |
Additional information: | ©ECMS Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani (Editors) ISBN: 978-0-9564944-8-1 / ISBN: 978-0-9564944-9-8 (CD) |
Keywords: | Evolution of cooperation, signed graphs, network dynamics, negative ties, agent-based models, degree heterogeneity |
UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10058695 |
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