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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
n V A Path to Human-Level AGI 16 AGI Preschool 289 16.1 Introduction 289 16.1.1 Contrast to Standard AI Evaluation Methodologies 290 16.2 Elements of Preschool Design 291 16.3 Elements of Preschool Curriculum 292 16.3.1 Preschool in the Light of Intelligence Theory 293 16.4 Task-Based Assessment in AGI P
parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. • Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money,
d "transfer learning," where the goal for an AI is to learn one task quicker given another task solved previously 10%117, TM95, EFTA00624066 16.2 Elements of Preschool Design 291 )1C05j. This is one of the capabilities an AI agent will need to simultaneously lear❑ different types of tasks as proposed in the Preschool sc
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
een eens 289 16.1 Introduction .......... 0.0000 teen teens 289 16.1.1 Contrast to Standard AI Evaluation Methodologies ................... 290 16.2 Elements of Preschool Design ...........00 0.00 e eee eee eee 291 16.3 Elements of Preschool Curriculum ........0... 00000 c eee eee eee 292 16.3.1 Preschool in the Light of Inte
e parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money, ST
fer learning,” where the goal for an AT is to learn one task quicker given another task solved previously [Car97, TM95, HOUSE_OVERSIGHT_013206 16.2 Elements of Preschool Design 291 BDS03, TSO07, RZDKO5]. This is one of the capabilities an AI agent will need to simultaneously learn different types of tasks as proposed in the
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