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Found 3 papers, 3 papers with code
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
We propose a general and model-free approach for Reinforcement Learning (RL) on real robotics with sparse rewards.
Grounded Language Learning in a Simulated 3D World
Trained via a combination of reinforcement and unsupervised learning, and beginning with minimal prior knowledge, the agent learns to relate linguistic symbols to emergent perceptual representations of its physical surroundings and to pertinent sequences of actions.
Latent Predictor Networks for Code Generation
Many language generation tasks require the production of text conditioned on both structured and unstructured inputs.
Ranked #10 on
Code Generation
on Django
