| Resumo: | We consider linear resource sharing problems
with multiple agents. Agents are heterogeneous, with heterogeneity modelled by a tuple of parameters taking value according to an underlying probability distribution, and share a fixed
resource amount. We provide an evaluation of a vital indicator
for the correct operation of the agents, namely, the probability
that the optimal resource share alters in case of a new agent
arrival. We view this problem under a data driven lens, and
provide a purely a-posteriori and prior-independent characterization of the above mentioned probability by exploiting recent
developments in the so called scenario approach theory. The
proposed framework is demonstrated on an economic dispatch
example in power systems, where agents can be thought of as
generating units participating in the power market.
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