Neuro-Symbolic Artificial Intelligence : : the State of the Art.

Neuro-Symbolic Artificial Intelligence : : the State of the Art.

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Superior document:Frontiers in Artificial Intelligence and Applications Series ; v.342
:
Hitzler, P.
TeilnehmendeR:
Sarker, M. K.
Place / Publishing House:Amsterdam : : IOS Press, Incorporated,, 2022.
Ã2022.
Year of Publication:2022
Edition:1st ed.
Language:English
Series:Frontiers in Artificial Intelligence and Applications Series
Online Access:
Physical Description:1 online resource (410 pages)
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ctrlnum (MiAaPQ)50029070505
(Au-PeEL)EBL29070505
(OCoLC)1311322262
collection bib_alma
record_format marc
spelling Hitzler, P.
Neuro-Symbolic Artificial Intelligence : the State of the Art.
1st ed.
Amsterdam : IOS Press, Incorporated, 2022.
Ã2022.
1 online resource (410 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Frontiers in Artificial Intelligence and Applications Series ; v.342
Intro -- Title Page -- Preface: The 3rd AI wave is coming, and it needs a theory -- Introduction -- Contents -- Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation -- Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example -- Chapter 3. Logic Meets Learning: From Aristotle to Neural Networks -- Chapter 4. Graph Reasoning Networks and Applications -- Chapter 5. Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases -- Chapter 6. Tractable Boolean and Arithmetic Circuits -- Chapter 7. Neuro-Symbolic AI = Neural + Logical + Probabilistic AI -- Chapter 8. A Constraint-Based Approach to Learning and Reasoning -- Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers -- Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning -- Chapter 11. Neuro-Symbolic Semantic Reasoning -- Chapter 12. Learning Reasoning Strategies in End-to-End Differentiable Proving -- Chapter 13. Generalizable Neuro-Symbolic Systems for Commonsense Question Answering -- Chapter 14. Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning -- Chapter 15. Human-Centered Concept Explanations for Neural Networks -- Chapter 16. Abductive Learning -- Chapter 17. Logic Tensor Networks: Theory and Applications -- Author Index.
Description based on publisher supplied metadata and other sources.
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Artificial intelligence.
Computational intelligence.
Neural computers.
Electronic books.
Sarker, M. K.
Print version: Hitzler, P. Neuro-Symbolic Artificial Intelligence: the State of the Art Amsterdam : IOS Press, Incorporated,c2022 9781643682440
ProQuest (Firm)
Frontiers in Artificial Intelligence and Applications Series
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=29070505 Click to View
language English
format eBook
author Hitzler, P.
spellingShingle Hitzler, P.
Neuro-Symbolic Artificial Intelligence : the State of the Art.
Frontiers in Artificial Intelligence and Applications Series ;
Intro -- Title Page -- Preface: The 3rd AI wave is coming, and it needs a theory -- Introduction -- Contents -- Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation -- Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example -- Chapter 3. Logic Meets Learning: From Aristotle to Neural Networks -- Chapter 4. Graph Reasoning Networks and Applications -- Chapter 5. Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases -- Chapter 6. Tractable Boolean and Arithmetic Circuits -- Chapter 7. Neuro-Symbolic AI = Neural + Logical + Probabilistic AI -- Chapter 8. A Constraint-Based Approach to Learning and Reasoning -- Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers -- Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning -- Chapter 11. Neuro-Symbolic Semantic Reasoning -- Chapter 12. Learning Reasoning Strategies in End-to-End Differentiable Proving -- Chapter 13. Generalizable Neuro-Symbolic Systems for Commonsense Question Answering -- Chapter 14. Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning -- Chapter 15. Human-Centered Concept Explanations for Neural Networks -- Chapter 16. Abductive Learning -- Chapter 17. Logic Tensor Networks: Theory and Applications -- Author Index.
author_facet Hitzler, P.
Sarker, M. K.
author_variant p h ph
author2 Sarker, M. K.
author2_variant m k s mk mks
author2_role TeilnehmendeR
author_sort Hitzler, P.
title Neuro-Symbolic Artificial Intelligence : the State of the Art.
title_sub the State of the Art.
title_full Neuro-Symbolic Artificial Intelligence : the State of the Art.
title_fullStr Neuro-Symbolic Artificial Intelligence : the State of the Art.
title_full_unstemmed Neuro-Symbolic Artificial Intelligence : the State of the Art.
title_auth Neuro-Symbolic Artificial Intelligence : the State of the Art.
title_new Neuro-Symbolic Artificial Intelligence :
title_sort neuro-symbolic artificial intelligence : the state of the art.
series Frontiers in Artificial Intelligence and Applications Series ;
series2 Frontiers in Artificial Intelligence and Applications Series ;
publisher IOS Press, Incorporated,
publishDate 2022
physical 1 online resource (410 pages)
edition 1st ed.
contents Intro -- Title Page -- Preface: The 3rd AI wave is coming, and it needs a theory -- Introduction -- Contents -- Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation -- Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example -- Chapter 3. Logic Meets Learning: From Aristotle to Neural Networks -- Chapter 4. Graph Reasoning Networks and Applications -- Chapter 5. Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases -- Chapter 6. Tractable Boolean and Arithmetic Circuits -- Chapter 7. Neuro-Symbolic AI = Neural + Logical + Probabilistic AI -- Chapter 8. A Constraint-Based Approach to Learning and Reasoning -- Chapter 9. Spike-Based Symbolic Computations on Bit Strings and Numbers -- Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning -- Chapter 11. Neuro-Symbolic Semantic Reasoning -- Chapter 12. Learning Reasoning Strategies in End-to-End Differentiable Proving -- Chapter 13. Generalizable Neuro-Symbolic Systems for Commonsense Question Answering -- Chapter 14. Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning -- Chapter 15. Human-Centered Concept Explanations for Neural Networks -- Chapter 16. Abductive Learning -- Chapter 17. Logic Tensor Networks: Theory and Applications -- Author Index.
isbn 9781643682457
9781643682440
callnumber-first Q - Science
callnumber-subject Q - General Science
callnumber-label Q335
callnumber-sort Q 3335 N48 42022
genre Electronic books.
genre_facet Electronic books.
url https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=29070505
illustrated Not Illustrated
dewey-hundreds 000 - Computer science, information & general works
dewey-tens 000 - Computer science, knowledge & systems
dewey-ones 006 - Special computer methods
dewey-full 6.3
dewey-sort 16.3
dewey-raw 6.3
dewey-search 6.3
oclc_num 1311322262
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