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Program Synthesis Guided Reinforcement Learning
A key challenge for reinforcement learning is solving long-horizon plann...
02/22/2021 ∙ by Yichen Yang, et al. ∙
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Neurosymbolic Transformers for Multi-Agent Communication
We study the problem of inferring communication structures that can solv...
01/05/2021 ∙ by Jeevana Priya Inala, et al. ∙
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Representing Partial Programs with Blended Abstract Semantics
Synthesizing programs from examples requires searching over a vast, comb...
12/23/2020 ∙ by Maxwell Nye, et al. ∙
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Program Synthesis with Pragmatic Communication
Program synthesis techniques construct or infer programs from user-provi...
07/09/2020 ∙ by Yewen Pu, et al. ∙
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Write, Execute, Assess: Program Synthesis with a REPL
We present a neural program synthesis approach integrating components wh...
06/09/2019 ∙ by Kevin Ellis, et al. ∙
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Verifiable Reinforcement Learning via Policy Extraction
While deep reinforcement learning has successfully solved many challengi...
05/22/2018 ∙ by Osbert Bastani, et al. ∙
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Learning to select examples for program synthesis
Program synthesis is a class of regression problems where one seeks a so...
11/09/2017 ∙ by Yewen Pu, et al. ∙
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Learning to Acquire Information
We consider the problem of diagnosis where a set of simple observations ...
04/20/2017 ∙ by Yewen Pu, et al. ∙
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sk_p: a neural program corrector for MOOCs
We present a novel technique for automatic program correction in MOOCs, ...
07/11/2016 ∙ by Yewen Pu, et al. ∙
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