  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 networks
show that when given the option, many agents become highly trustworthy; most or
all become highly trustworthy when knowledge of their neighbors'
trustworthiness is based on past interactions rather than known a priori. This
trustworthiness is not the result of altruism, instead agents are intrinsically
motivated to become trustworthy partners by competition. Two insights are
presented: first, trustworthy behavior drives an increase in the utility of all
agents, where maintaining a relatively modest level of trustworthiness may
easily improve net utility by as much as 14.5%. If only one agent exhibits
modest trust among self-centered ones, it can increase its average utility by
up to 25% in certain cases! Second, and counter-intuitively, when partnership
opportunities are abundant agents become less trustworthy.
