The IBAL framework builds information-theoretic attacks that break agent interactions in MARL and trains policies to stay robust under observation and action perturbations.
Implementation Details We provide additional implementation details for our attacks and training pipeline
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Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning
The IBAL framework builds information-theoretic attacks that break agent interactions in MARL and trains policies to stay robust under observation and action perturbations.