License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.7.5.56
URN: urn:nbn:de:0030-drops-82803
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/8280/
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Besold, Tarek R. ; d'Avila Garcez, Artur ; Lamb, Luis C.
Weitere Beteiligte (Hrsg. etc.): Tarek R. Besold and Artur d'Avila Garcez and Luis C. Lamb

Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192)

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dagrep_v007_i005_p056_17192.pdf (2 MB)

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 17192 "Human-Like Neural-Symbolic Computing", held from May 7th to 12th, 2017. The underlying idea of Human-Like Computing is to incorporate into Computer Science aspects of how humans learn, reason and compute. Whilst recognising the relevant scientific trends in big data and deep learning, capable of achieving state-of-the-art performance in speech recognition and computer vision tasks, limited progress has been made towards understanding the principles underlying language and vision understanding. Under the assumption that neural-symbolic computing - the study of logic and connectionism as well statistical approaches - can offer new insight into this problem, the seminar brought together computer scientists, but also specialists on artificial intelligence, cognitive science, machine learning, knowledge representation and reasoning, computer vision, neural computation, and natural language processing. The seminar consisted of contributed and invited talks, breakout and joint group discussion sessions, and a hackathon. It was built upon previous seminars and workshops on the integration of computational learning and symbolic reasoning, such as the Neural-Symbolic Learning and Reasoning (NeSy) workshop series, and the previous Dagstuhl Seminar 14381: Neural-Symbolic Learning and Reasoning.

BibTeX - Entry

@Article{besold_et_al:DR:2017:8280,
  author =	{Tarek R. Besold and Artur d'Avila Garcez and Luis C. Lamb},
  title =	{{Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192)}},
  pages =	{56--83},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{7},
  number =	{5},
  editor =	{Tarek R. Besold and Artur d'Avila Garcez and Luis C. Lamb},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/8280},
  URN =		{urn:nbn:de:0030-drops-82803},
  doi =		{10.4230/DagRep.7.5.56},
  annote =	{Keywords: Deep Learning, Human-like computing, Multimodal learning, Natural language processing, Neural-symbolic integration}
}

Keywords: Deep Learning, Human-like computing, Multimodal learning, Natural language processing, Neural-symbolic integration
Collection: Dagstuhl Reports, Volume 7, Issue 5
Issue Date: 2017
Date of publication: 20.12.2017

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