Optimal search from multiple distributions with infinite horizon

With infinite horizon, optimal rules for sequential search from a known distribution feature a constant reservation value that is independent of whether recall of past options is possible. We extend this result to the case when there are multiple distributions to choose from: it is optimal to sample from the same distribution in every period and to continue searching until a constant reservation value is reached.