Related papers: Modular Neural Computer

Modular Neural Computer

URL: http://arxiv.org/abs/2603.13323v1
Date: Wed, 04 Mar 2026 16:29:20 GMT
Title: Modular Neural Computer
Abstract summary: The Modular Neural Computer (MNC) is a memory-augmented neural architecture for exact computation on variable-length inputs.<n>The architecture is illustrated through three case studies: computing the minimum of an array, sorting an array in place, and executing A* search on a fixed problem instance.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: This paper introduces the Modular Neural Computer (MNC), a memory-augmented neural architecture for exact algorithmic computation on variable-length inputs. The model combines an external associative memory of scalar cells, explicit read and write heads, a controller multi-layer perceptron (MLP), and a homogeneous set of functional MLP modules. Rather than learning an algorithm end to end from data, it realizes a given algorithm through analytically specified neural components with fixed interfaces and exact behavior. The control flow is represented inside the neural computation through one-hot module gates, where inactive modules are inhibited. Computation unfolds as a sequence of memory transformations generated by a fixed graph. The architecture is illustrated through three case studies: computing the minimum of an array, sorting an array in place, and executing A* search on a fixed problem instance. These examples show that algorithmic procedures can be compiled into modular neural components with external memory while preserving deterministic behavior and explicit intermediate state.

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