policy
CybORG-CAGE-1-Public
Mel-Meijer · PyTorch
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Overview
Name
CybORG-CAGE-1-Public
Author
Mel-Meijer
Framework
PyTorch
License
unknown
Skill type
navigation
Evidence level
untested
Task description
BSc Computer Science with Security and Forensics Final Project. Explores the capability of autonomous deep reinforcement learning models to defend a network against a simulated attacker in the CAGE challenge 1 environment scenario. Trains and compares PPO, DQN, and A2C in their ability to defend a n
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 CybORG-CAGE-1-Public yet.
Datasets that reference this policy
0No datasets reference CybORG-CAGE-1-Public yet.