Epstein Secrets

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,

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-Formal Model of Glocal Memory

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

: that is, one instance synaptic modification causes another instance of synaptic modification, which causes another, and so forth' 113i0II. 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies Hebbian learning is conventionally formulated in terms of individual neurons, but, it can be extended natur

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

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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

on: that is, one instance synaptic modification causes another instance of synaptic modification, which causes another, and so forth? [Bi01]. 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies Hebbian learning is conventionally formulated in terms of individual neurons, but, it can be extended natura