policy
PCP-Dreamer
IAMHUT · PyTorch
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Overview
Name
PCP-Dreamer
Author
IAMHUT
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
This code implements PCP-Dreamer, a world-model reinforcement learning algorithm with Prospective Cognitive Pruning (PCP). An RSSM is trained with reconstruction and balanced KL losses, and policies are optimized in latent imagination using pathwise derivatives and lambda-returns.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
0+20 mentioned but not in catalog yetNo robots list PCP-Dreamer as compatible yet. Know of one? Flag it above.
Compatible environments
0No environments list PCP-Dreamer yet.
Datasets that reference this policy
0No datasets reference PCP-Dreamer yet.