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of intel- ligence and mind. It then sketches the broad outlines of a novel, integrative architecture for Artificial General Intelligence (AGT) called CogPrime ... and describes an approach for giving a young AGI system (CogPrime or otherwise) appropriate experience, so that it can develop its own smarts, cr
oduction .......00..000 000 tte teen ee 271 14.2: Key Vertex atid Edge Typé$ casas cuine cs ce ees ee ses ems es emo ws Meee MERE OE 271 14.3 Derived Hypergraphs .......... 0.000. c cece tenet eae 272 14.3.1 SMEPH Vertices .........000 0000. tte 272 14.3.2 SMEPH Edges ...... 0... ee eee eens 273 14.4 Implicat
works... .......0.000. 0022 c cee ee 268 13.6.4 Neural-Symbolic Glocality in CogPrime ............. 0000.0 269 14 Representing Implicit Knowledge via Hypergraphs ....................... 271 14.1 Introduction .......00..000 000 tte teen ee 271 14.2: Key Vertex atid Edge Typé$ casas cuine cs ce ees ee ses ems es
epresentation...................... 245 13.1 Introduction ..........000 0002 eens 245 13.2 Localized Knowledge Representation using Weighted, Labeled Hypergraphs .... 246 13.2.1 Weighted, Labeled Hypergraphs............... 0000: c eee eee eee eee 246 13.3 Atoms: Their Types and Weights ............ 0.00. cee
f intel- ligence and mind. It then sketches the broad outlines of a novel, integrative architecture for Artificial General Intelligence (AGI) called CogPrime ... and describes an approach for giving a young AGI system (CogPrime or otherwise) appropriate experience, so that it can develop its own smarts,
the Brain 263 13.6.3 Glocal Hopfield Networks 268 13.6.4 Neural-Symbolic Glocality in CogPrime 269 14 Representing Implicit Knowledge via Hypergraphs 271 14.1 Introduction 271 14.2 Key Vertex and Edge Types 271 14.3 Derived Hypergraphs 272 14.3.1 SMEPH Vertices 272 14.3.2 SMEPH Ed
13 Local, Global and Glocal Knowledge Representation 245 13.1 Introduction 245 13.2 Localized Knowledge Representation using Weighted, Labeled Hypergraphs 246 13.2.1 Weighted, Labeled Hypergraphs 246 13.3 Atoms: Their Types and Weights 247 13.3.1 Some Basic Atom Types 247 13.3.2 Variable At
what this "tuning" should involve - namely, making a system possessing mind-state sequences that correspond meaningfully to world-state sequences. CogPrime's overall design and particular cognitive processes are reasonably well interpreted as an attempt to achieve this for everyday human goals and envir
algorithms for creating localist knowledge from globalist knowledge are described 13.2 Localized Knowledge Representation using Weighted, Labeled Hypergraphs There are many different mechanisms for representing knowledge in AI systems in an explicit, localized way, most of them descending from various va
ut what this "tuning" should involve — namely, making a system possessing mind-state sequences that correspond meaningfully to world-state sequences. CogPrime’s overall design and particular cognitive processes are reasonably well interpreted as an attempt to achieve this for everyday human goals and enviro
n” algorithms for creating localist knowledge from globalist knowledge are described 13.2 Localized Knowledge Representation using Weighted, Labeled Hypergraphs There are many different mechanisms for representing knowledge in AI systems in an explicit, localized way, most of them descending from various var
Entities connected to both CogPrime and Hypergraphs

Marc Rich
PERSONOpenCog
ORGANIZATIONDeSTIN
ORGANIZATION
George W. Bush
PERSONConceptNodes
ORGANIZATION
Stephen Hawking
PERSONHopfield
ORGANIZATION
Joel Pitt
PERSON
Vince Foster
PERSONHebbian Learning
ORGANIZATIONNil Geisweiller
PERSON
Joscha Bach
PERSONCassio Pennachin
PERSON
Vladimir Putin
PERSON
Marvin Minsky
PERSONBill Hibbard
PERSONArtificial General Intelligence
ORGANIZATIONStephan Vladimir Bugaj
PERSON
Edelman
ORGANIZATIONMicroPsi
ORGANIZATION