UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Programming with a differentiable forth interpreter

Bošnjak, M; Rocktäschel, T; Naradowsky, J; Riedel, S; (2017) Programming with a differentiable forth interpreter. In: Proceedings of the 34th International Conference on Machine Learning. (pp. pp. 547-556). PMLR: Sydney, Australia. Green open access

[img]
Preview
Text
1605.06640v3.pdf - ["content_typename_Published version" not defined]

Download (740kB) | Preview

Abstract

Given that in practice training data is scarce for all but a small set of problems, a core question is how to incorporate prior knowledge into a model. In this paper, we consider the case of prior procedural knowledge for neural networks, such as knowing how a program should traverse a sequence, but not what local actions should be performed at each step. To this end, we present an end-to-end differentiable interpreter for the programming language Forth which enables programmers to write program sketches with slots that can be filled with behaviour trained from program input-output data. We can optimise this behaviour directly through gradient descent techniques on user-specified objectives, and also integrate the program into any larger neural computation graph. We show empirically that our interpreter is able to effectively leverage different levels of prior program structure and learn complex behaviours such as sequence sorting and addition. When connected to outputs of an LSTM and trained jointly, our interpreter achieves state-of-the-art accuracy for end-to-end reasoning about quantities expressed in natural language stories.

Type: Proceedings paper
Title: Programming with a differentiable forth interpreter
Event: ICLR 2017
ISBN-13: 9781510855144
Open access status: An open access version is available from UCL Discovery
Publisher version: http://proceedings.mlr.press/v70/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/10052992
Downloads since deposit
8Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item