The emergent behavior of a distributed system is conditioned by the
information available to the local decision-makers. Therefore, one may expect
that providing decision-makers with more information will improve system
performance; in this work, we find that this is not necessarily the case. In
multi-agent maximum coverage problems, we find that even when agents'
objectives are aligned with the global welfare, informing agents about the
realization of the resource's random values can reduce equilibrium performance
by a factor of 1/2. This affirms an important aspect of designing distributed
systems: information need be shared carefully. We further this understanding by
providing lower and upper bounds on the ratio of system welfare when
information is (fully or partially) revealed and when it is not, termed the
value-of-informing. We then identify a trade-off that emerges when optimizing
the performance of the best-case and worst-case equilibrium.Comment: To appear: LCS