SUN: Reaching for Novelty in Reinforcement Learning
This paper proposes SUccessor-to-Novelty (SUN), an indicator derived from successor value functions to identify goals that are both novel and reachable and presents an adaptive goal-selection strategy that leverages these properties, and an accurate yet lightweight pseudocount to avoid the overhead of classic methods.
Wen-Yan Yang, A. Mustafin, Dominik Baumann et al.
· 0 citations