CyberWorld: World Models for Sample-Efficient Autonomous Cyber Defense
cs.LG, cs.AI, cs.CR
Submitted: 2026-09-25
Updated: 2026-09-25
Terminology
Sources
- Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation
- Small Language Models are the Future of Agentic AI
- Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties
- Mastering Diverse Domains through World Models
- Learning Ad Hoc Network Dynamics via Graph-Structured World Models
- Automated Cyber Defense with Generalizable Graph-based Reinforcement Learning Agents
- ACDZero: MCTS Agent for Mastering Automated Cyber Defense
- Trident: How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)
- Proximal Policy Optimization Algorithms
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