Degrees of Separation, Social Learning, and the Evolution of Cooperation in a Small-World Network
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Authors
Seltzer, Nicholas
Smirnov, Oleg
Issue Date
2015
Type
Citation
Language
en_US
Keywords
Simulation , Social networks , Agent-Based , Modern society , Cooperation , Small-World
Alternative Title
Abstract
We analyze a novel agent-based model of a social network in which agents make contributions to others conditional upon the social distance, which we measure in terms of the "degrees of separation" between the two players. On the basis of a simple imitation model, the emerging strategy profile is characterized by high levels of cooperation with those who are directly connected to the agent and lower but positive levels of cooperation with those who are indirectly connected to the agent. Increasing maximum interaction distance decreases cooperation with close neighbors but increases cooperation with distant neighbors for a net negative effect. On the other hand, allowing agents to learn and imitate socially distant neighbors increases cooperation for all types of interaction. Combining greater interaction distance with greater learning distance leads to a positive change in the total social welfare produced by the agents' contributions.
Description
Citation
Seltzer, N., & Smirnov, O. (2015). Degrees of Separation, Social Learning, and the Evolution of Cooperation in a Small-World Network. Journal of Artificial Societies and Social Simulation, 18(4). doi:10.18564/jasss.2851
Publisher
Journal of Artificial Societies and Social Simulation
License
Journal
Volume
Issue
PubMed ID
ISSN
1460-7425