Skip to main content
Book ChapterOPEN ACCESS

Architecture

Springer Science and Business Media Deutschland GmbH, (2022), 65-72
DOI: 10.1007/978-3-031-08020-3_8
0Citations
Citations of this article
104Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Machine learning excels at inducing mappings from data, but struggles to induce causal hierarchies. In contrast, symbolic reasoning (in particular, when considered as an expression language) can represent any form of domain knowledge and can index into code or data via pattern matching.

Cite

CITATION STYLE

APA

Swan, J., Nivel, E., Kant, N., Hedges, J., Atkinson, T., & Steunebrink, B. (2022). Architecture. In Studies in Computational Intelligence (Vol. 1049, pp. 65–72). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-08020-3_8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free