Limited-Trust in Social Network Games
Timothy Murray, Jugal Garg, Rakesh Nagi

TL;DR
This paper models trustworthiness in social network games, showing that agents tend to become more trustworthy through interactions, which increases overall utility, but trustworthiness decreases when opportunities are plentiful.
Contribution
It introduces a game-theoretic model of limited-trust in social networks and demonstrates how trustworthiness evolves and impacts utility through empirical simulations.
Findings
Trustworthy agents increase overall utility by up to 14.5%.
Agents can boost their utility by up to 25% by being modestly trustworthy.
Trustworthiness decreases when partnership opportunities are abundant.
Abstract
We consider agents in a social network competing to be selected as partners in collaborative, mutually beneficial activities. We study this through a model in which an agent i can initiate a limited number k_i>0 of games and selects the ideal partners from its one-hop neighborhood. On the flip side it can accept as many games offered from its neighbors. Each game signifies a productive joint economic activity, and players attempt to maximize their individual utilities. Unsurprisingly, more trustworthy agents are more desirable as partners. Trustworthiness is measured by the game theoretic concept of Limited-Trust, which quantifies the maximum cost an agent is willing to incur in order to improve the net utility of all agents. Agents learn about their neighbors' trustworthiness through interactions and their behaviors evolve in response. Empirical trials performed on realistic social…
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Taxonomy
TopicsGame Theory and Applications · Experimental Behavioral Economics Studies · Opinion Dynamics and Social Influence
