MoCoDA: Model-based Counterfactual Data Augmentation

The number of states in a dynamic process is exponential in the number of objects, making reinforcement learning (RL) difficult in complex, multi-object domains. For agents to scale to the real world, they will need to react to and reason about unseen combinations of objects. We argue that the abili...

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Hauptverfasser:	Pitis, Silviu, Creager, Elliot, Mandlekar, Ajay, Garg, Animesh
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Computer Science - Robotics
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