  In service exchange platforms, anonymous users exchange services with each
other: clients request services and are matched to servers who provide
services. Because providing good-quality services requires effort, in any
single interaction a server will have no incentive to exert effort and will
shirk. We show that if current servers will later become clients and want
good-quality services, shirking can be eliminated by rating protocols, which
maintain ratings for each user, prescribe behavior in each client-server
interaction, and update ratings based on whether observed/reported behavior
conforms with prescribed behavior. The rating protocols proposed are the first
to achieve social optimum even when observation/reporting is imperfect (quality
is incorrectly assessed/reported or reports are lost). The proposed protocols
are remarkably simple, requiring only binary ratings and three possible
prescribed behaviors. Key to the efficacy of the proposed protocols is that
they are nonstationary, and tailor prescriptions to both current and past
rating distributions.
