Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents

arXiv cs.AI · 18 hours ago

Researchers proposed a policy learning technique using imitation learning to help autonomous cyber-defense agents predict attacker actions in partially observable network environments. The method integrates with neurosymbolic agents using behavior trees with learning-enabled components to defend networks while maintaining operations. The approach achieves high prediction accuracy across simulated scenarios with different attacker policies.