policy
Reinforcement-Learning-by-Minimizing-Constraint-Violation
phalonneNana · PyTorch
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Overview
Name
Reinforcement-Learning-by-Minimizing-Constraint-Violation
Author
phalonneNana
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
This research aims to address the challenge of effectively representing logical safety constraints within the RL framework by introducing a novel violation measure, thereby enhancing the agent’s decision- making process in model-free RL using constrained Markov Decision Processes to adhere to the sa
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
20anybotics-anymal-cnot in seedalohanot in seedgoogle-barkour-vbnot in seedboston-dynamics-spotnot in seedfranka-fr3not in seedgoogle-barkour-v0not in seedagilex-pipernot in seedberkeley-humanoidnot in seedbitcraze-crazyflie-2not in seedanybotics-anymal-bnot in seedagility-cassienot in seedarx-l5not in seedbooster-t1not in seedfranka-emika-pandanot in seedfranka-fr3-v2not in seeddynamixel-2rnot in seedflexiv-rizon4not in seedassetsnot in seedapptronik-apollonot in seedfourier-n1not in seed
Compatible environments
0No environments list Reinforcement-Learning-by-Minimizing-Constraint-Violation yet.
Datasets that reference this policy
0No datasets reference Reinforcement-Learning-by-Minimizing-Constraint-Violation yet.