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05/12/2022
Asking for Knowledge: Training RL Agents to Query External Knowledge Using Language
To solve difficult tasks, humans ask questions to acquire knowledge from...
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08/06/2021
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning
Solving complex real-world tasks, e.g., autonomous fleet control, often ...
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07/23/2021
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Exploration is critical for good results in deep reinforcement learning ...
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04/14/2021
GridToPix: Training Embodied Agents with Minimal Supervision
While deep reinforcement learning (RL) promises freedom from hand-labele...
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12/17/2020
High-Throughput Synchronous Deep RL
Deep reinforcement learning (RL) is computationally demanding and requir...
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10/31/2019
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning
Sample efficiency and scalability to a large number of agents are two im...
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04/11/2019