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Realpe-Gómez, John
Vilone, Daniele
Andrighetto, Giulia
Nardin, Luis G.
Montoya Zegarra, Javier Alexander
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[Journal:] Games [ISSN:] 2073-4336 [Volume:] 9 [Year:] 2018 [Issue:] 4 [Pages:] 1-14
In this work, we explore the role of learning dynamics and social norms in human cooperation on networks. We study the model recently introduced in [Physical Review E, 97, 042321 (2018)] that integrates the well-studied Experience Weighted Attraction learning model with some features characterizing human norm psychology, namely the set of cognitive abilities humans have evolved to deal with social norms. We provide further evidence that this extended model-that we refer to as Experience Weighted Attraction with Norm Psychology-closely reproduces cooperative patterns of behavior observed in large-scale experiments with humans. In particular, we provide additional support for the finding that, when deciding to cooperate, humans balance between the choice that returns higher payoffs with the choice in agreement with social norms. In our experiment, agents play a prisoner's dilemma game on various network structures: (i) a static lattice where agents have a fixed position; (ii) a regular random network where agents have a fixed position; and (iii) a dynamic lattice where agents are randomly re-positioned at each game iteration. Our results show that the network structure does not affect the dynamics of cooperation, which corroborates results of prior laboratory experiments. However, the network structure does seem to affect how individuals balance between their self-interested and normative choices.
social norms
learning mechanisms
network reciprocity
computer simulations
laboratory experiments
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