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research1d ago

Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents

aarXivscore 0.24

Researchers propose a method to learn red agent policy from observations for neurosymbolic autonomous cyber agents. The approach uses reinforcement learning and behavior trees with learning-enabled components. This method aims to improve autonomous cyber-defense in partially observable systems. You can apply this approach to develop more adaptive security systems.

Key takeaways

  • Uses reinforcement learning and behavior trees with learning-enabled components.
  • Aims to improve autonomous cyber-defense in partially observable systems.
  • Method learns red agent policy from observations.
#reinforcement-learning#neurosymbolic-ai#cyber-security
Read the original
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research1d ago

Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents

aarXiv

Researchers propose a method to learn red agent policy from observations for neurosymbolic autonomous cyber agents. The approach uses reinforcement learning and behavior trees with learning-enabled components. This method aims to improve autonomous cyber-defense in partially observable systems. You can apply this approach to develop more adaptive security systems.

Key takeaways

  • Uses reinforcement learning and behavior trees with learning-enabled components.
  • Aims to improve autonomous cyber-defense in partially observable systems.
  • Method learns red agent policy from observations.
#reinforcement-learning#neurosymbolic-ai#cyber-security
Read at arXiv