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Found 3 papers, 1 papers with code
Theoretical foundations for programmatic reinforcement learning
The field of Reinforcement Learning (RL) is concerned with algorithms for learning optimal policies in unknown stochastic environments.
WikiCoder: Learning to Write Knowledge-Powered Code
WikiCoder solves tasks that no program synthesizers were able to solve before thanks to the use of knowledge graphs, while integrating with recent developments in the field to operate at scale.
Scaling Neural Program Synthesis with Distribution-based Search
We investigate how to augment probabilistic and neural program synthesis methods with new search algorithms, proposing a framework called distribution-based search.
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