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We introduce Nocturne, a new 2D driving simulator for investigating multi-agent coordination under partial observability.
Interaction effects in parafoveal letter recognition
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The numpy array: a structure for efficient numerical computation
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Efficient bvh construction via approximate agglomerative clustering
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
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Carla: An open urban driving simulator
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Multi-agent connected autonomous driving using deep reinforcement learning
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Deepdrive zero, 2020
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Smarts: Scalable multi-agent reinforcement learning training school for autonomous driving
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Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
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The hanabi challenge: A new frontier for ai research
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Bark: Open behavior benchmarking in multi-agent environments
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nuscenes: A multimodal dataset for autonomous driving
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Summit: A simulator for urban driving in massive mixed traffic
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Vectornet: Encoding hd maps and agent dynamics from vectorized representation
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One thousand and one hours: Self-driving motion prediction dataset
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Drivergym: Democratising reinforcement learning for autonomous driving
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Scalable evaluation of multi-agent reinforcement learning with melting pot
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Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning
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Madras: Multi agent driving simulator
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Trafficsim: Learning to simulate realistic multi-agent behaviors
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Argoverse 2: Next generation datasets for self-driving perception and forecasting
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The surprising effectiveness of ppo in cooperative, multi-agent games
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