Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning

  title={Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning},
  author={Anirudha Majumdar and Vincent Pacelli},
—Our goal is to develop theory and algorithms for establishing fundamental limits on performance for a given task imposed by a robot’s sensors. In order to achieve this, we define a quantity that captures the amount of task-relevant information provided by a sensor. Using a novel version of the generalized Fano inequality from information theory, we demonstrate that this quantity provides an upper bound on the highest achievable expected reward for one-step decision making tasks. We then extend… 
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