# Neural Programmer-Interpreters

Authors: Scott Reed, Nando de Freitas.

Learns neural programs that share a recurrent interpreter and a program memory.

ArXiv initial submission: 2015-11-19.

[Original paper](https://arxiv.org/abs/1511.06279) · [Reading-list entry](https://programasweights.com/reading-list/papers/1511.06279/)
[Preprint BibTeX](https://programasweights.com/reading-list/papers/1511.06279/citation.bib) · [Preprint CSL-JSON](https://programasweights.com/reading-list/papers/1511.06279/citation.csl.json) · [JSON record](https://programasweights.com/reading-list/papers/1511.06279/record.json)

**Contribution:** Learns from execution traces and composes subprograms for addition, sorting, and 3D-object canonicalization.

**Program form:** Program embeddings stored in a key-value memory.

**Conditioning:** A program identifier, arguments, and observations of the environment.

**Execution:** A recurrent interpreter calls subprograms and takes actions in the environment.

**Relationship to PAW:** PAW cites this work on learned program representations and shared interpreters.

**Limitations:** Training requires execution traces and task-specific interfaces.

[Discussion in the paper](https://arxiv.org/html/2607.02512v1#S10)

Related terms: neural programmer-interpreter, neural programs, program memory, compositional execution.

## Published version

Neural Programmer-Interpreters. Scott Reed, Nando de Freitas. International Conference on Learning Representations, 2016.
[Publication](https://arxiv.org/abs/1511.06279) · [BibTeX](https://programasweights.com/reading-list/papers/1511.06279/publication.bib) · [CSL-JSON](https://programasweights.com/reading-list/papers/1511.06279/publication.csl.json)
[Publication record](https://arxiv.org/pdf/1511.06279).

## Approaches

- [Programs and reusable artifacts](https://programasweights.com/reading-list/guides/fuzzy-functions/): Learn programs that can be saved and run on new inputs.

Reading-list version 1.2.0; updated 2026-10-19.