The Road to General Intelligence.

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Superior document:Studies in Computational Intelligence Series ; v.1049
:
TeilnehmendeR:
Place / Publishing House:Cham : : Springer International Publishing AG,, 2022.
©2022.
Year of Publication:2022
Edition:1st ed.
Language:English
Series:Studies in Computational Intelligence Series
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Physical Description:1 online resource (142 pages)
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id 5007021221
ctrlnum (MiAaPQ)5007021221
(Au-PeEL)EBL7021221
(OCoLC)1333445371
collection bib_alma
record_format marc
spelling Swan, Jerry.
The Road to General Intelligence.
1st ed.
Cham : Springer International Publishing AG, 2022.
©2022.
1 online resource (142 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Studies in Computational Intelligence Series ; v.1049
Intro -- Foreword by Melanie Mitchell -- Foreword by David Spivak -- Contents -- 1 Introduction -- Part I Requirements -- 2 Background -- 2.1 What we Mean by General Intelligence -- 2.2 Science as Extended Mind -- 2.3 The Death of `Good Old-Fashioned AI' -- 3 Where is My Mind? -- 3.1 A Sanity Check -- 3.2 Real-World Machine Learning -- 4 Challenges for Deep Learning -- 4.1 Compositionality -- 4.2 Strong Typing -- 4.3 Reflection -- 4.4 Implications and Summary -- 5 Challenges for Reinforcement Learning -- 5.1 A Priori Reward Specification -- 5.2 Sampling: Safety and Efficiency -- 6 Work on Command: The Case for Generality -- 6.1 Goals and Constraints -- 6.2 Planning -- 6.3 Anytime Operation -- Part II Semantically Closed Learning -- 7 Philosophy -- 7.1 The Problem of Machine Induction -- 7.2 Semantically Closed Learning (SCL) -- 7.3 Baseline Properties of SCL -- 7.4 High-Level Inference Mechanisms of SCL -- 7.5 Intrinsic Motivation and Unsupervised Learning -- 8 Architecture -- 8.1 SCL as a Distributed/Localist Hybrid -- 8.2 Reference Architecture -- 9 A Compositional Framework -- 9.1 Categorical Cybernetics -- 9.2 Hypothesis Generation -- 9.3 Abstraction and Analogy -- 9.4 Abduction -- 10 2nd Order Automation Engineering -- 10.1 Behavioral System Engineering -- 10.2 Reactive Synthesis -- 10.3 Proactive Synthesis -- 10.4 Safety -- 11 Prospects -- 11.1 Summary -- 11.2 Research Topics -- 11.2.1 Choice of Expression Language -- 11.2.2 Compositional Primitives -- 11.2.3 Links with Behavioral Control -- 11.2.4 Pragmatics via `Causal Garbage Collection' -- 11.3 Conclusion -- Appendix Bibliography.
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.
Electronic books.
Nivel, Eric.
Kant, Neel.
Hedges, Jules.
Atkinson, Timothy.
Steunebrink, Bas.
Print version: Swan, Jerry The Road to General Intelligence Cham : Springer International Publishing AG,c2022 9783031080197
ProQuest (Firm)
Studies in Computational Intelligence Series
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=7021221 Click to View
language English
format eBook
author Swan, Jerry.
spellingShingle Swan, Jerry.
The Road to General Intelligence.
Studies in Computational Intelligence Series ;
Intro -- Foreword by Melanie Mitchell -- Foreword by David Spivak -- Contents -- 1 Introduction -- Part I Requirements -- 2 Background -- 2.1 What we Mean by General Intelligence -- 2.2 Science as Extended Mind -- 2.3 The Death of `Good Old-Fashioned AI' -- 3 Where is My Mind? -- 3.1 A Sanity Check -- 3.2 Real-World Machine Learning -- 4 Challenges for Deep Learning -- 4.1 Compositionality -- 4.2 Strong Typing -- 4.3 Reflection -- 4.4 Implications and Summary -- 5 Challenges for Reinforcement Learning -- 5.1 A Priori Reward Specification -- 5.2 Sampling: Safety and Efficiency -- 6 Work on Command: The Case for Generality -- 6.1 Goals and Constraints -- 6.2 Planning -- 6.3 Anytime Operation -- Part II Semantically Closed Learning -- 7 Philosophy -- 7.1 The Problem of Machine Induction -- 7.2 Semantically Closed Learning (SCL) -- 7.3 Baseline Properties of SCL -- 7.4 High-Level Inference Mechanisms of SCL -- 7.5 Intrinsic Motivation and Unsupervised Learning -- 8 Architecture -- 8.1 SCL as a Distributed/Localist Hybrid -- 8.2 Reference Architecture -- 9 A Compositional Framework -- 9.1 Categorical Cybernetics -- 9.2 Hypothesis Generation -- 9.3 Abstraction and Analogy -- 9.4 Abduction -- 10 2nd Order Automation Engineering -- 10.1 Behavioral System Engineering -- 10.2 Reactive Synthesis -- 10.3 Proactive Synthesis -- 10.4 Safety -- 11 Prospects -- 11.1 Summary -- 11.2 Research Topics -- 11.2.1 Choice of Expression Language -- 11.2.2 Compositional Primitives -- 11.2.3 Links with Behavioral Control -- 11.2.4 Pragmatics via `Causal Garbage Collection' -- 11.3 Conclusion -- Appendix Bibliography.
author_facet Swan, Jerry.
Nivel, Eric.
Kant, Neel.
Hedges, Jules.
Atkinson, Timothy.
Steunebrink, Bas.
author_variant j s js
author2 Nivel, Eric.
Kant, Neel.
Hedges, Jules.
Atkinson, Timothy.
Steunebrink, Bas.
author2_variant e n en
n k nk
j h jh
t a ta
b s bs
author2_role TeilnehmendeR
TeilnehmendeR
TeilnehmendeR
TeilnehmendeR
TeilnehmendeR
author_sort Swan, Jerry.
title The Road to General Intelligence.
title_full The Road to General Intelligence.
title_fullStr The Road to General Intelligence.
title_full_unstemmed The Road to General Intelligence.
title_auth The Road to General Intelligence.
title_new The Road to General Intelligence.
title_sort the road to general intelligence.
series Studies in Computational Intelligence Series ;
series2 Studies in Computational Intelligence Series ;
publisher Springer International Publishing AG,
publishDate 2022
physical 1 online resource (142 pages)
edition 1st ed.
contents Intro -- Foreword by Melanie Mitchell -- Foreword by David Spivak -- Contents -- 1 Introduction -- Part I Requirements -- 2 Background -- 2.1 What we Mean by General Intelligence -- 2.2 Science as Extended Mind -- 2.3 The Death of `Good Old-Fashioned AI' -- 3 Where is My Mind? -- 3.1 A Sanity Check -- 3.2 Real-World Machine Learning -- 4 Challenges for Deep Learning -- 4.1 Compositionality -- 4.2 Strong Typing -- 4.3 Reflection -- 4.4 Implications and Summary -- 5 Challenges for Reinforcement Learning -- 5.1 A Priori Reward Specification -- 5.2 Sampling: Safety and Efficiency -- 6 Work on Command: The Case for Generality -- 6.1 Goals and Constraints -- 6.2 Planning -- 6.3 Anytime Operation -- Part II Semantically Closed Learning -- 7 Philosophy -- 7.1 The Problem of Machine Induction -- 7.2 Semantically Closed Learning (SCL) -- 7.3 Baseline Properties of SCL -- 7.4 High-Level Inference Mechanisms of SCL -- 7.5 Intrinsic Motivation and Unsupervised Learning -- 8 Architecture -- 8.1 SCL as a Distributed/Localist Hybrid -- 8.2 Reference Architecture -- 9 A Compositional Framework -- 9.1 Categorical Cybernetics -- 9.2 Hypothesis Generation -- 9.3 Abstraction and Analogy -- 9.4 Abduction -- 10 2nd Order Automation Engineering -- 10.1 Behavioral System Engineering -- 10.2 Reactive Synthesis -- 10.3 Proactive Synthesis -- 10.4 Safety -- 11 Prospects -- 11.1 Summary -- 11.2 Research Topics -- 11.2.1 Choice of Expression Language -- 11.2.2 Compositional Primitives -- 11.2.3 Links with Behavioral Control -- 11.2.4 Pragmatics via `Causal Garbage Collection' -- 11.3 Conclusion -- Appendix Bibliography.
isbn 9783031080203
9783031080197
callnumber-first Q - Science
callnumber-subject Q - General Science
callnumber-label Q342
callnumber-sort Q 3342
genre Electronic books.
genre_facet Electronic books.
url https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=7021221
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 006.3
dewey-sort 16.3
dewey-raw 006.3
dewey-search 006.3
oclc_num 1333445371
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