Approximate Next Policy Sampling approximates the next policy's state distribution during training to enable larger safe policy updates in deep RL, demonstrated by SV-PPO matching or exceeding standard PPO on Atari and continuous control tasks.
Hugging the walls mitigates the negative effect of an erroneous move
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
-
Approximate Next Policy Sampling: Replacing Conservative Target Policy Updates in Deep RL
Approximate Next Policy Sampling approximates the next policy's state distribution during training to enable larger safe policy updates in deep RL, demonstrated by SV-PPO matching or exceeding standard PPO on Atari and continuous control tasks.