Epstein Secrets

ning 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-Formal Model of Glocal Memory 262 13.6.2 Glocal Memory in the Brain 263 13.6.3 Glocal Hopfield Networks 268 13.6.4 Neural-Symbolic Glocality in CogPrime 269 14 Repre

EPH Vertices 272 14.3.2 SMEPH Edges 273 14.4 Implications of Patternist Philosophy for Derived Hypergraphs of Intelligent Systems 274 14.4.1 SMEPH Principles in CogPrime 276 15 Emergent Networks of Intelligence 279 15.1 Introduction 279 15.2 Small World Networks 280 15.3 Dual Network Structure

ficant role in the brain and in intelligent systems more broadly. EFTA00624037 262 13 Local, Global and Glocal Knowledge Representation 13.6.1 A Semi-Formal Model of Glocal Memory To explain the notion of glocal memory more precisely, we will introduce a simple semi-formal model of a system $ that uses a memory to record info

hen according to the patternist philosophy evolution of its derived hypergraph can't necessarily be expected to follow the above principles. 14.4.1 SMEPH Principles in CogPrime We now more explicitly elaborate the application of these ideas in the CogPrime context. As noted above, in addition to explicit knowle

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rnist Philosophy for Derived Hypergraphs of Intelligent SYSUCIIS ss cm ems FERS HEME HEME OEE OS CREME CR EMS CR EMS ORES OR EME OR EE Ome 274 14.4.1 SMEPH Principles in CogPrime ............. 000... c eee eee 276 15 Emergent Networks of Intelligence..............00... 002. c eee eee 279 L5el JPOAWEtIOH, «205 seme

ole in the brain and in intelligent systems more broadly. HOUSE_OVERSIGHT_013177 262 13 Local, Global and Glocal Knowledge Representation 13.6.1 A Semi-Formal Model of Glocal Memory To explain the notion of glocal memory more precisely, we will introduce a simple semi-formal model of a system S that uses a memory to record infor

then according to the patternist philosophy evolution of its derived hypergraph can’t necessarily be expected to follow the above principles. 14.4.1 SMEPH Principles in CogPrime We now more explicitly elaborate the application of these ideas in the CogPrime context. As noted above, in addition to explicit knowled