期刊
KNOWLEDGE-BASED SYSTEMS
卷 171, 期 -, 页码 1-24出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2018.12.018
关键词
Multi-agent systems; Evolutionary computing; Tag-based cooperation; Altruism; Conformity; Social influence
Designing cooperation-enhancing protocols for large-scale multiagent networked systems has been a grand transdisciplinary challenge. In recent years, tag-based interactions and conformity bias have been studied extensively but separately as two viable mechanisms for cooperation enhancement in such systems. Inspired by recent studies on interaction effects in social dilemmas, we herein develop a hybrid, multiagent-based, co-evolutionary model of tag-mediated cooperation and conformity with conditional and unconditional strategies. Through a series of extensive Monte Carlo simulation experiments, we study four variants of this computational model, finding that under the majority rule, the nonconforming unconditional cooperators and conformity biased transmission of other strategies can lead to global altruistic dominance. Employing a random pinning control mechanism, we further observe that only a small fraction of nonconforming altruists is actually required to drive the system towards a robust persistence of pure altruism. Our analytic results in combination with further computational experiments reveal that spatial structure and nonconformity of cooperators are the two indispensable ingredients for the stable dominance of altruistic behavior in tag-based multiagent systems. Our findings can be beneficial for developing novel cooperation-controlling techniques in distributed self-organizing systems such as peer-to-peer networks or in various social networking and viral marketing technologies. (C) 2018 Elsevier B.V. All rights reserved.
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