privateboss/Network_Defense_Symmetric_Competitive

102,400,000 timesteps, Multi-Agent Reinforcement Learning Total Environment Steps= 10 parallel environments × 7,000 episodes ×2,048 steps= 102400000 Timesteps -The Red Agent’s goal is to discover vulnerabilities, elevate privileges, compromise assets, and maintain persistence. Its action space can be modeled after phases of the MITRE ATT&CK framework. -The Blue Agent’s goal is to maintain system availability, reduce the attack surface, detect malicious behavior… See the full description on the dataset page: https://huggingface.co/datasets/privateboss/Network_Defense_Sy

<iframe src="https://silytics.si/embed/item/f4271869-4837-4248-bc4a-56ce530558f9" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.