Adaptive Variance for Changing Sparse-Reward Environments

Xingyu Lin, Pengsheng Guo, Carlos Florensa +1

Robots that are trained to perform a task in a fixed environment often fail when facing unexpected changes to the environment due to a lack of exploration. We propose a principled…