An attention-augmented actor-critic agent learns to dynamically weight multiple environment views by importance and outperforms baselines on TORCS and three other 3D simulators under noise and partial observability.
Torcs, the open racing car simulator
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An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments
An attention-augmented actor-critic agent learns to dynamically weight multiple environment views by importance and outperforms baselines on TORCS and three other 3D simulators under noise and partial observability.