mlsanityData to 7 Oct 2026

Learning Cyber Defence Tactics from Scratch with Multi-Agent Reinforcement Learning

arXiv 2310.05939 ↗First posted 25 Aug 2023cs.CR cs.AI cs.LGcited by 12

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Abstract (arXiv)

Recent advancements in deep learning techniques have opened new possibilities for designing solutions for autonomous cyber defence. Teams of intelligent agents in computer network defence roles may reveal promising avenues to safeguard cyber and kinetic assets. In a simulated game environment, agents are evaluated on their ability to jointly mitigate attacker activity in host-based defence scenarios. Defender systems are evaluated against heuristic attackers with the goals of compromising network confidentiality, integrity, and availability. Value-based Independent Learning and Centralized Training Decentralized Execution (CTDE) cooperative Multi-Agent Reinforcement Learning (MARL) methods are compared revealing that both approaches outperform a simple multi-agent heuristic defender. This work demonstrates the ability of cooperative MARL to learn effective cyber defence tactics against varied threats.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 26 of its 68 references that are in the map. First posted on arXiv 25 Aug 2023.

Builds on

26 of 68 references.

References · 26

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
  3. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
  4. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  5. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  6. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  7. 2017Rainbow: Combining Improvements in Deep Reinforcement Learningcited by 774
  8. 2018QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 697
  9. 2019The StarCraft Multi-Agent Challengecited by 589
  10. 2017Value-Decomposition Networks For Cooperative Multi-Agent Learningcited by 490
  11. 2020Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Taskscited by 207
  12. 2020RODE: Learning Roles to Decompose Multi-Agent Taskscited by 125
14 more
  1. 2022SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learningcited by 118
  2. 2019Deep Reinforcement Learning for Cyber Securitycited by 92
  3. 2020Qatten: A General Framework for Cooperative Multiagent Reinforcement Learningcited by 81
  4. 2021Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learningcited by 68
  5. 2021CybORG: A Gym for the Development of Autonomous Cyber Agentscited by 58
  6. 2019From Few to More: Large-scale Dynamic Multiagent Curriculum Learningcited by 36
  7. 2020Finding Effective Security Strategies through Reinforcement Learning and Self-Playcited by 32
  8. 2021Network Environment Design for Autonomous Cyberdefensecited by 29
  9. 2022Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policiescited by 22
  10. 2023Automated Cyber Defence: A Reviewcited by 19
  11. 2023A Multiagent CyberBattleSim for RL Cyber Operation Agentscited by 8
  12. 2022Transformer-based Value Function Decomposition for Cooperative Multi-agent Reinforcement Learning in StarCraftcited by 5
  13. 2023SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learningcited by 3
  14. 2023Enabling A Network AI Gym for Autonomous Cyber Agentscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 7; 2026: 2.

12 papers.

  1. 2024Optimal Defender Strategies for CAGE-2 using Causal Modeling and Tree Searchcited by 12
  2. 2023Deep Reinforcement Learning for Autonomous Cyber Defence: A Surveycited by 6
  3. 2025Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agentscited by 4
  4. 2025Large Language Model Integration with Reinforcement Learning to Augment Decision-Making in Autonomous Cyber Operationscited by 3
  5. 2024Multi-Agent Actor-Critics in Autonomous Cyber Defensecited by 2
  6. 2025Learning to Communicate in Multi-Agent Reinforcement Learning for Autonomous Cyber Defencecited by 2
  7. 2025A Comparative Evaluation of Teacher-Guided Reinforcement Learning Techniques for Autonomous Cyber Operationscited by 2
  8. 2025Towards Production-Worthy Simulation for Autonomous Cyber Operationscited by 2
  9. 2025Quantitative Resilience Modeling for Autonomous Cyber Defensecited by 1
  10. 2025PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defensecited by 0
  11. 2026Learning Communication Between Heterogeneous Agents in Multi-Agent Reinforcement Learning for Autonomous Cyber Defencecited by 0
  12. 2026Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operationscited by 0