From Connectivity to Rewards: Dense Reward Learning with Directed State Graphs
This paper introduces a state connectivity model designed to predict pairwise state connectivity strength in asymmetric environments, and transforms these connectivity strengths into scalar auxiliary dense rewards, providing continuous guidance across multiple hierarchical levels.
Shuyuan Zhang, Zi-Han Wang, Xiao-Wen Chang et al.
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