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Documents authored by d'Avila Garcez, Artur

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d'Avila Garcez, Artur

Document
DOI: 10.4230/DagRep.7.5.56
Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192)

Authors: Tarek R. Besold, Artur d'Avila Garcez, and Luis C. Lamb

Published in: Dagstuhl Reports, Volume 7, Issue 5 (2018)

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.
Cite as

Tarek R. Besold, Artur d'Avila Garcez, and Luis C. Lamb. Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192). In Dagstuhl Reports, Volume 7, Issue 5, pp. 56-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{besold_et_al:DagRep.7.5.56,
  author =	{Besold, Tarek R. and d'Avila Garcez, Artur and Lamb, Luis C.},
  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 =	{Besold, Tarek R. and d'Avila Garcez, Artur and Lamb, Luis C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.7.5.56},
  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}
}
Document
DOI: 10.4230/DagRep.4.9.50
Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381)

Authors: Artur d'Avila Garcez, Marco Gori, Pascal Hitzler, and Luís C. Lamb

Published in: Dagstuhl Reports, Volume 4, Issue 9 (2015)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 14381 "Neural-Symbolic Learning and Reasoning", which was held from September 14th to 19th, 2014. This seminar brought together specialist in machine learning, knowledge representation and reasoning, computer vision and image understanding, natural language processing, and cognitive science. The aim of the seminar was to explore the interface among several fields that contribute to the effective integration of cognitive abilities such as learning, reasoning, vision and language understanding in intelligent and cognitive computational systems. The seminar consisted of contributed and invited talks, breakout and joint group discussion sessions.
Cite as

Artur d'Avila Garcez, Marco Gori, Pascal Hitzler, and Luís C. Lamb. Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381). In Dagstuhl Reports, Volume 4, Issue 9, pp. 50-84, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@Article{davilagarcez_et_al:DagRep.4.9.50,
  author =	{d'Avila Garcez, Artur and Gori, Marco and Hitzler, Pascal and Lamb, Lu{\'\i}s C.},
  title =	{{Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381)}},
  pages =	{50--84},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{4},
  number =	{9},
  editor =	{d'Avila Garcez, Artur and Gori, Marco and Hitzler, Pascal and Lamb, Lu{\'\i}s C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.9.50},
  URN =		{urn:nbn:de:0030-drops-48843},
  doi =		{10.4230/DagRep.4.9.50},
  annote =	{Keywords: Neural-symbolic computation, deep learning, image understanding, lifelong machine learning, natural language understanding, ontology learning}
}
Document
DOI: 10.4230/OASIcs.ICCSW.2013.89
Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents

Authors: Leo de Penning, Artur D'Avila Garcez, and John-Jules C. Meyer

Published in: OASIcs, Volume 35, 2013 Imperial College Computing Student Workshop

Abstract
Deep Boltzmann Machines (DBM) have been used as a computational cognitive model in various AI-related research and applications, notably in computational vision and multimodal fusion. Being regarded as a biological plausible model of the human brain, the DBM is also becoming a popular instrument to investigate various cortical processes in neuroscience. In this paper, we describe how a multimodal DBM is implemented as part of a Neural-Symbolic Cognitive Agent (NSCA) for real-time multimodal fusion and inference of streaming audio and video data. We describe how this agent can be used to simulate certain neurological mechanisms related to hallucinations and dreaming and how these mechanisms are beneficial to the integrity of the DBM. Finally, we will explain how the NSCA is used to extract multimodal information from the DBM and provide a compact and practical iconographic temporal logic formula for complex relations between visual and auditory patterns.
Cite as

Leo de Penning, Artur D'Avila Garcez, and John-Jules C. Meyer. Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents. In 2013 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 35, pp. 89-94, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{depenning_et_al:OASIcs.ICCSW.2013.89,
  author =	{de Penning, Leo and D'Avila Garcez, Artur and Meyer, John-Jules C.},
  title =	{{Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents}},
  booktitle =	{2013 Imperial College Computing Student Workshop},
  pages =	{89--94},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-63-7},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{35},
  editor =	{Jones, Andrew V. and Ng, Nicholas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2013.89},
  URN =		{urn:nbn:de:0030-drops-42765},
  doi =		{10.4230/OASIcs.ICCSW.2013.89},
  annote =	{Keywords: Multimodal fusion, Deep Boltzmann Machine, Neural-Symbolic Cognitive Agent, Dreaming, Hallucinations}
}

D'Avila Garcez, Artur

Document
DOI: 10.4230/DagRep.7.5.56
Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192)

Authors: Tarek R. Besold, Artur d'Avila Garcez, and Luis C. Lamb

Published in: Dagstuhl Reports, Volume 7, Issue 5 (2018)

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.
Cite as

Tarek R. Besold, Artur d'Avila Garcez, and Luis C. Lamb. Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192). In Dagstuhl Reports, Volume 7, Issue 5, pp. 56-83, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

Copy BibTex To Clipboard

@Article{besold_et_al:DagRep.7.5.56,
  author =	{Besold, Tarek R. and d'Avila Garcez, Artur and Lamb, Luis C.},
  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 =	{Besold, Tarek R. and d'Avila Garcez, Artur and Lamb, Luis C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.7.5.56},
  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}
}
Document
DOI: 10.4230/DagRep.4.9.50
Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381)

Authors: Artur d'Avila Garcez, Marco Gori, Pascal Hitzler, and Luís C. Lamb

Published in: Dagstuhl Reports, Volume 4, Issue 9 (2015)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 14381 "Neural-Symbolic Learning and Reasoning", which was held from September 14th to 19th, 2014. This seminar brought together specialist in machine learning, knowledge representation and reasoning, computer vision and image understanding, natural language processing, and cognitive science. The aim of the seminar was to explore the interface among several fields that contribute to the effective integration of cognitive abilities such as learning, reasoning, vision and language understanding in intelligent and cognitive computational systems. The seminar consisted of contributed and invited talks, breakout and joint group discussion sessions.
Cite as

Artur d'Avila Garcez, Marco Gori, Pascal Hitzler, and Luís C. Lamb. Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381). In Dagstuhl Reports, Volume 4, Issue 9, pp. 50-84, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

Copy BibTex To Clipboard

@Article{davilagarcez_et_al:DagRep.4.9.50,
  author =	{d'Avila Garcez, Artur and Gori, Marco and Hitzler, Pascal and Lamb, Lu{\'\i}s C.},
  title =	{{Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381)}},
  pages =	{50--84},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2015},
  volume =	{4},
  number =	{9},
  editor =	{d'Avila Garcez, Artur and Gori, Marco and Hitzler, Pascal and Lamb, Lu{\'\i}s C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.9.50},
  URN =		{urn:nbn:de:0030-drops-48843},
  doi =		{10.4230/DagRep.4.9.50},
  annote =	{Keywords: Neural-symbolic computation, deep learning, image understanding, lifelong machine learning, natural language understanding, ontology learning}
}
Document
DOI: 10.4230/OASIcs.ICCSW.2013.89
Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents

Authors: Leo de Penning, Artur D'Avila Garcez, and John-Jules C. Meyer

Published in: OASIcs, Volume 35, 2013 Imperial College Computing Student Workshop

Abstract
Deep Boltzmann Machines (DBM) have been used as a computational cognitive model in various AI-related research and applications, notably in computational vision and multimodal fusion. Being regarded as a biological plausible model of the human brain, the DBM is also becoming a popular instrument to investigate various cortical processes in neuroscience. In this paper, we describe how a multimodal DBM is implemented as part of a Neural-Symbolic Cognitive Agent (NSCA) for real-time multimodal fusion and inference of streaming audio and video data. We describe how this agent can be used to simulate certain neurological mechanisms related to hallucinations and dreaming and how these mechanisms are beneficial to the integrity of the DBM. Finally, we will explain how the NSCA is used to extract multimodal information from the DBM and provide a compact and practical iconographic temporal logic formula for complex relations between visual and auditory patterns.
Cite as

Leo de Penning, Artur D'Avila Garcez, and John-Jules C. Meyer. Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents. In 2013 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 35, pp. 89-94, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

Copy BibTex To Clipboard

@InProceedings{depenning_et_al:OASIcs.ICCSW.2013.89,
  author =	{de Penning, Leo and D'Avila Garcez, Artur and Meyer, John-Jules C.},
  title =	{{Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents}},
  booktitle =	{2013 Imperial College Computing Student Workshop},
  pages =	{89--94},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-63-7},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{35},
  editor =	{Jones, Andrew V. and Ng, Nicholas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2013.89},
  URN =		{urn:nbn:de:0030-drops-42765},
  doi =		{10.4230/OASIcs.ICCSW.2013.89},
  annote =	{Keywords: Multimodal fusion, Deep Boltzmann Machine, Neural-Symbolic Cognitive Agent, Dreaming, Hallucinations}
}
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