DHRL defines belief-equivalence over augmented states to abstract away control-redundant states, preserving optimality in finite domains and yielding a deep actor-critic method that outperforms baselines on MuJoCo tasks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Delayed homomorphic reinforcement learning for environments with delayed feedback
DHRL defines belief-equivalence over augmented states to abstract away control-redundant states, preserving optimality in finite domains and yielding a deep actor-critic method that outperforms baselines on MuJoCo tasks.