  We consider a collection of statistically identical two-state continuous time
Markov chains (channels). A controller continuously selects a channel with the
view of maximizing infinite horizon average reward. A switching cost is paid
upon channel changes. We consider two cases: full observation (all channels
observed simultaneously) and partial observation (only the current channel
observed). We analyze the difference in performance between these cases for
various policies. For the partial observation case with two channels, or an
infinite number of channels, we explicitly characterize an optimal threshold
for two sensible policies which we name "call-gapping" and "cool-off". Our
results present a qualitative view on the interaction of the number of
channels, the available information, and the switching costs.
