simulation to University of Delaware's scaled smart city with adversarial multi-agent
reinforcement learning, in which an adversary attempts to decrease the net reward by
perturbing both the inputs and outputs of the autonomous vehicles during training. We train
the autonomous vehicles to coordinate with each other while crossing a roundabout in the
presence of an adversary in simulation. The adversarial policy successfully reproduces the …