CybORG++加速网络防御强化学习研究，性能提升千倍。
CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agents
- 基于CAGE 2改进，支持更快训练与自定义
- 引入MiniCAGE轻量版本，平行迭代提速1000倍
- 适合网络安全、强化学习方向研究者使用
CybORG++ 是一个面向网络防御强化学习研究的先进工具包，基于 CAGE 2 CybORG 环境构建。它提升了调试能力，优化了智能体实现支持，并简化了环境结构，使训练更快、定制更便捷。修复了前代多个软件缺陷，新增 MiniCAGE 轻量版，可在并行迭代中实现最高达 1000 倍的执行速度提升，同时保持准确性和核心功能。该平台为开发和评估防御性智能体提供了强大支持，是推动企业级网络防御研究的重要资源。
原文摘要 · Abstract (English)
CybORG++ is an advanced toolkit for reinforcement learning research focused on network defence. Building on the CAGE 2 CybORG environment, it introduces key improvements, including enhanced debugging capabilities, refined agent implementation support, and a streamlined environment that enables faster training and easier customisation. Along with addressing several software bugs from its predecessor, CybORG++ introduces MiniCAGE, a lightweight version of CAGE 2, which improves performance dramatically, up to 1000x faster execution in parallel iterations, without sacrificing accuracy or core functionality. CybORG++ serves as a robust platform for developing and evaluating defensive agents, making it a valuable resource for advancing enterprise network defence research.
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