Uber AI, Engineering
Leveraging Constraint Logic Programming for Neural Guided Program Synthesis
April 1, 2018 / GlobalAbstract
We present a method for solving Programming by Example (PBE) problems that tightly integrates a neural network with a constraint logic programming system called miniKanren. Internally, miniKanren searches for a program that satisfies the recursive constraints imposed by the provided examples. Our Recurrent Neural Network (RNN) model uses these constraints as input to score candidate programs. We show evidence that using our method to guide miniKanren’s search is a promising approach to solving PBE problems.
Authors
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E Byrd, Raquel Urtasun, Richard S. Zemel
Conference
ICLR 2018
Full Paper
Uber ATG
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