AIBullisharXiv – CS AI · 6h ago7/10
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Formal Verification of Learned Multi-Agent Communication Policies via Decision Tree Distillation
Researchers present the first formal verification framework for multi-agent reinforcement learning (MARL) communication policies by distilling neural networks into interpretable decision trees and verifying them with probabilistic model checking. The approach achieves 97.9% fidelity to original policies while enabling safety verification for critical robotic applications like drone swarms and autonomous vehicle fleets.