property resource experiment with comparable parameters to the ones set in the simulations
run in this study. They report a 40-point increase in efficiency. In designs where rational
agents should be unaffected by strategy space choice, the level of resource appropriation is
influenced by the strategy space size both for human and genetic algorithm agents. Although
to a lower degree than Walker, Gardner, and Ostrom (1990), also public good experiments by
Laury and Holt (1998) have revealed a such systematic impact on aggregate cooperation
levels of the strategy space. According to them, the most important determinant of the size
and direction of these impacts on cooperation appears to be the equilibrium's location relative
to the group's potential contributions.12
Another design change to the common property resource experiment is the introduction of a
decentralized monitoring and sanctioning system. Consider a situation where after having
privately decided his own exploitation level of the common property resource, each agent has
the option of selecting other individuals for inspection. At a unitary cost, the inspector can
view the decision of any individual. If the inspected individual has exploited the resource
excessively, relative to a publicly known amount, a fine is imposed and paid to the inspector.
In the opposite case, no fine is paid. As the eventual fine is always transferred to the
inspector, an agent can make a profit by requesting an inspection on a “heavy” free rider. An
experiment in this environment is reported in Casari and Plott (2003) using two sets of
parameters values for the sanctioning system. Simulation carried out with genetic algorithm
yields aggregate results that are in-between the Nash equilibrium outcome and the human
data. Not only GA agents outperform Nash equilibrium predictions at the aggregate level,
12 “When the Nash equilibrium falls between the lower boundary and the mid-point of the decision space,
average contributions typically exceed the equilibrium level. (...) The most important determinant of the size
and direction of these deviations appears to be the equilibrium's location relative to the group's aggregate
endowment. For example, significant under-contribution is observed when the equilibrium is relatively close to
the upper boundary.” (Laury and Holt, 1998)
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