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Introduction to the TPLP Special Issue on User-oriented Logic Programming and Reasoning Paradigms

Published online by Cambridge University Press:  15 February 2019

STEFAN ELLMAUTHALER  and
CLAUDIA SCHULZ
STEFAN ELLMAUTHALER
Affiliation:
Leipzig University, Leipzig, Germany (e-mail: ellmauthaler@informatik.uni-leipzig.de)
CLAUDIA SCHULZ
Affiliation:
Ubiquitous Knowledge Processing (UKP) Lab, TU Darmstadt, Darmstadt, Germany (e-mail: schulz@ukp.informatik.tu-darmstadt.de)
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With the rise of machine learning, and more recently the overwhelming interest in deep learning, knowledge representation and reasoning (KRR) approaches struggle to maintain their position within the wider Artificial Intelligence (AI) community. Often considered as part of the good old-fashioned AI (Haugeland 1985) – like a memory of glorious old days that have come to an end – many consider KRR as no longer applicable (on its own) to the problems faced by AI today (Blackwell 2015; Garnelo et al. 2016). What they see are logical languages with symbols incomprehensible by most, inference mechanisms that even experts have difficulties tracing and debugging, and the incapability to process unstructured data like text.

Information

Type
Editorial
Information
Theory and Practice of Logic Programming , Volume 19 , Special Issue 2: User-Oriented Logic Programming and Reasoning Paradigms , March 2019 , pp. 109 - 113
Copyright
Copyright © Cambridge University Press 2019 

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