Jacobian-based selection of messages, agents, and timesteps combined with two new adversarial loss functions disrupts multi-agent RL communication more effectively than random perturbations in navigation, PredatorPrey, and TrafficJunction environments.
Communication learning via back- propagation in discrete channels with unknown noise,
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Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications
Jacobian-based selection of messages, agents, and timesteps combined with two new adversarial loss functions disrupts multi-agent RL communication more effectively than random perturbations in navigation, PredatorPrey, and TrafficJunction environments.