Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/80045
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Type: Journal article
Title: Coevolution of quantum and classical strategies on evolving random networks
Author: Li, Q.
Iqbal, A.
Perc, M.
Chen, M.
Abbott, D.
Citation: PLoS One, 2013; 8(7):1-10
Publisher: Public Library of Science
Issue Date: 2013
ISSN: 1932-6203
1932-6203
Editor: Barrat, A.
Statement of
Responsibility: 
Qiang Li, Azhar Iqbal, Matjaž Perc, Minyou Chen, Derek Abbott
Abstract: We study the coevolution of quantum and classical strategies on weighted and directed random networks in the realm of the prisoner’s dilemma game. During the evolution, agents can break and rewire their links with the aim of maximizing payoffs, and they can also adjust the weights to indicate preferences, either positive or negative, towards their neighbors. The network structure itself is thus also subject to evolution. Importantly, the directionality of links does not affect the accumulation of payoffs nor the strategy transfers, but serves only to designate the owner of each particular link and with it the right to adjust the link as needed. We show that quantum strategies outperform classical strategies, and that the critical temptation to defect at which cooperative behavior can be maintained rises, if the network structure is updated frequently. Punishing neighbors by reducing the weights of their links also plays an important role in maintaining cooperation under adverse conditions. We find that the self-organization of the initially random network structure, driven by the evolutionary competition between quantum and classical strategies, leads to the spontaneous emergence of small average path length and a large clustering coefficient.
Keywords: Biological Evolution
Game Theory
Models, Biological
Rights: © 2013 Li et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
DOI: 10.1371/journal.pone.0068423
Grant ID: http://purl.org/au-research/grants/arc/DP0771453
Published version: http://dx.doi.org/10.1371/journal.pone.0068423
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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