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1 The Hopfield neural net model 256 13.4.2 Knowledge Representation via Cell Assemblies 257 13.5 Neural Foundations of Learning 258 13.5.1 Hebbian Learning 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies 258 13.5.3 Neural Darwinism 259 13.6 Glocal Memory 260 13.6.1 A Semi-Fo
11.4.4 The Reflexive Stage 202 EFTA00623772 Contents xvii 12 The Engineering and Development of Ethics 205 12.1 Introduction 205 12.2 Review of Current Thinking on the Risks of AGI 206 12.3 The Value of an Explicit Goal System 209 12.4 Ethical Synergy 210 12.4.1 Stages of Development of Declarative Ethics 211 12.4.2 S
e our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of
receives. It's a very complex matter that is richly intermixed with all the other aspects of intelligence, and here we will treat it as such. 12.2 Review of Current Thinking on the Risks of AGI Before proceeding to outline our own perspective on AGI ethics in the context of CogPrime, we will review the main existing strains of thought on t
3.4.2 Knowledge Representation via Cell Assemblies .................2.05- 257 13.5 Neural Foundations of Learning ..........0 0.000 ee eee 258 13.5.1 Hebbian Learning............ 0.0.00 eee ete eee 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies .......... 258 35:38 Netital DArwitiiSitt +2; case
d Development of Ethics..........................005. 205 121 JPOAWMEtIOH, «205 sa2ms emees Cees ENNeS LE SMES MEME OEMS SERS EME!s dees em; 205 12.2 Review of Current Thinking on the Risks of AGI ................ 00.0002 eee 206 12.3 The Value of an Explicit Goal System. ....... 0.0... eee ee ee 209 12.4 Ethical Synergy ...... 0.00. eee eee te
ake our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of
t receives. It’s a very complex matter that is richly intermixed with all the other aspects of intelligence, and here we will treat it as such. 12.2 Review of Current Thinking on the Risks of AGI Before proceeding to outline our own perspective on AGI ethics in the context of CogPrime, we will review the main existing strains of thought on th
Entities connected to both Hebbian Learning and Review of Current Thinking on the Risks of AGI

Marc Rich
PERSON
George W. Bush
PERSONOpenCog
ORGANIZATIONCogPrime
ORGANIZATION
Stephen Hawking
PERSONStephan Vladimir Bugaj
PERSON
Joel Pitt
PERSON
Vladimir Putin
PERSONBill Hibbard
PERSONKey Vertex
LOCATIONSMEPH Principles
ORGANIZATIONSemi-Formal Model of Glocal Memory
ORGANIZATIONHopfield
ORGANIZATIONSusan Greenfield
PERSONGlocal Hopfield Networks
ORGANIZATIONSMEPH Edges
ORGANIZATIONthe Stages of Ethical Development
ORGANIZATION
Hypergraphs
PERSONAGI Ethics
ORGANIZATIONIntegrative Ethics
ORGANIZATION