Can genetic algorithms explain experimental anomalies? An application to common property resources

Individual heterogeneity can be measured either with SD2 or D2. Both indexes yields
similar conclusions. The standard deviation for human agents SD2H=9.05 is not statistically
different than for inexperience and experienced GA (SD2GA=5.76 for T=32 and SD2GA=4.79
for T=64) at 0.05 level but is significantly different from the long term value (SD2GA=4.09
for T=400, Table 1). The same ranking emerges when using the difference between the
minimum and the maximum, D2. Individual heterogeneity for Super-experienced GA is
smaller than for inexperienced GA (D2GA=15.66 with T=400 vs. D2GA=22.78 with T=32);
still, human agents are more heterogeneous than inexperienced GA (D2H=28.35).⁸

Had the agents been designed with differentiated goals or variable skills, the heterogeneity
of behavior would have not been surprising. Although bounded, the GA agents are endowed
with identical levels of rationality. Yet they generate individually distinct behavior. These
results are found in several experimental studies, where identical incentives are given and
heterogeneous behavior is observed (Laury and Holt, 1998, Cox and Walker, 1998, Palfrey
and Prisbrey, 1997, Saijo and Nakamura, 1995).

The only built-in individual diversity among genetic algorithm agents is the random
initialization of the strategies. In other words, agents do not have common priors. Moreover,
there are four other stochastic operators that might introduce variability in the data: the
reinforcement rule, the choice rule, crossover, and mutation. In order to have a benchmark to
evaluate the influence of the random element in the results, the GA outcome can be
compared with the results of interactions among zero intelligence agents and among noisy
Nash agents.

Zero intelligence agents are designed in the spirit of Gode and Sunder (1993) and are
essentially pure noise.⁹ The individual strategy for each agent ^~x_i is drawn from a uniform

⁸ Even when the simulation is very long, 10,000 periods, individual heterogeneity does not disappear.

⁹ In Gode and Sunder(1993) they are subject to a budget constraint as well.

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