mlsanityData to 14 Oct 2026

Reinforcement Learning-based Threat Assessment

arXiv 2503.02612 ↗First posted 4 Mar 2025cs.LG cs.AIcited by 0

On the map: Deep reinforcement learning methods → Adversarial robustness and RL in finance

Abstract (arXiv)

In some game scenarios, due to the uncertainty of the number of enemy units and the priority of various attributes, the evaluation of the threat level of enemy units as well as the screening has been a challenging research topic, and the core difficulty lies in how to reasonably set the priority of different attributes in order to achieve quantitative evaluation of the threat. In this paper, we innovatively transform the problem of threat assessment into a reinforcement learning problem, and through systematic reinforcement learning training, we successfully construct an efficient neural network evaluator. The evaluator can not only comprehensively integrate the multidimensional attribute features of the enemy, but also effectively combine our state information, thus realizing a more accurate and scientific threat assessment.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Adversarial robustness and RL in finance, one of 15 directions in Deep reinforcement learning methods. Builds on 5 of its 8 references that are in the map. First posted on arXiv 4 Mar 2025.

Builds on

5 of 8 references.

References · 5

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2015Continuous control with deep reinforcement learningcited by 3,407
  3. 2017Rainbow: Combining Improvements in Deep Reinforcement Learningcited by 786
  4. 2017Value-Decomposition Networks For Cooperative Multi-Agent Learningcited by 503
  5. 2023DanZero+: Dominating the GuanDan Game through Reinforcement Learningcited by 6

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  2. 2025A Framework for Adversarial Analysis of Decision Support Systems Prior to Deployment
  3. 2026Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutions
  4. 2026PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses
  5. 2025Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning
  6. 2025Reinforcement Learning for Decision-Level Interception Prioritization in Drone Swarm Defense
  7. 2024Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack
  8. 2025Evaluation-Aware Reinforcement Learning