  Agents acting in the natural world aim at selecting appropriate actions based
on noisy and partial sensory observations. Many behaviors leading to decision
mak- ing and action selection in a closed loop setting are naturally phrased
within a control theoretic framework. Within the framework of optimal Control
Theory, one is usually given a cost function which is minimized by selecting a
control law based on the observations. While in standard control settings the
sensors are assumed fixed, biological systems often gain from the extra
flexibility of optimiz- ing the sensors themselves. However, this sensory
adaptation is geared towards control rather than perception, as is often
assumed. In this work we show that sen- sory adaptation for control differs
from sensory adaptation for perception, even for simple control setups. This
implies, consistently with recent experimental results, that when studying
sensory adaptation, it is essential to account for the task being performed.
