  We consider a two-road dynamic routing game where the state of one of the
roads (the "risky road") is stochastic and may change over time. This generates
room for experimentation. A central planner may wish to induce some of the
(finite number of atomic) agents to use the risky road even when the expected
cost of travel there is high in order to obtain accurate information about the
state of the road. Since agents are strategic, we show that in order to
generate incentives for experimentation the central planner however needs to
limit the number of agents using the risky road when the expected cost of
travel on the risky road is low. In particular, because of congestion, too much
use of the risky road when the state is favorable would make experimentation no
longer incentive compatible. We characterize the optimal incentive compatible
recommendation system, first in a two-stage game and then in an
infinite-horizon setting. In both cases, this system induces only partial,
rather than full, information sharing among the agents (otherwise there would
be too much exploitation of the risky road when costs there are low).
