Sharing compressed latent states and planned waypoints between agents, triggered by prediction errors, improves multi-agent driving performance in CARLA while cutting communication bandwidth by roughly 50x.
With Assumption Assumption 3 holds, we obtain the following bound, rl − ˆrl ≤Lr(1 + Lπ)ϵt+l Qt+L − ˆQt+L ≤LQ(1 + Lπ)ϵt+L, where LQ := Lr 1−γ
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Ego-centric Learning of Communicative World Models for Autonomous Driving
Sharing compressed latent states and planned waypoints between agents, triggered by prediction errors, improves multi-agent driving performance in CARLA while cutting communication bandwidth by roughly 50x.