Before revision:  Value learning over belief spaces suffer from computational challenges in high-dimensional spaces, such as large spatial environments and long temporal horizons for exploration. At the same time, it should be adaptive and resilient to disturbances at run time in order to ensure the robot's safety, as required in many real-world applications .
After revision:  Value learning over belief spaces suffer from computational challenges in high-dimensional spaces, such as large spatial environments and long temporal horizons suffers from severe computational challenges. Moreover, constructed policies must safely adapt to unexpected changes in the belief at runtime .