Introduction to the special issue on probability, logic and learning

Cussens, James, de Raedt, Luc, Kimmig, Angelika ORCID: https://orcid.org/0000-0002-6742-4057 and Sato, Taisuke 2015. Introduction to the special issue on probability, logic and learning. Theory and Practice of Logic Programming 15 (02) , pp. 145-146. 10.1017/S1471068413000665

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Abstract

Recently, the combination of probability, logic and learning has received considerable attention in the artificial intelligence and machine learning communities; see e.g. Getoor and Taskar (2007); De Raedt et al. (2008). Computational logic often plays a major role in these developments since it forms the theoretical backbone for much of the work in probabilistic programming and logical and relational learning. Contemporary work in this area is often application- and experiment-driven, but is also concerned with the theoretical foundations of formalisms and inference procedures and with advanced implementation technology that scales well.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Cambridge University Press (CUP)
ISSN:	1471-0684
Date of First Compliant Deposit:	20 November 2017
Date of Acceptance:	7 November 2012
Last Modified:	16 Nov 2024 04:00
URI:	https://orca.cardiff.ac.uk/id/eprint/106736

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