Epstein Secrets

mpo- rary philosophers Daniel Dennett [Den91J and Douglas Hofstadter 1110179, I lo1961, in Benjamin Whorl'

th Values and Attention Values 255 13.4 Knowledge Representation via Attractor Neural Networks 256 EFTA00623773 xviii Contents 13.4.1 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 Learni

ve pattern recognition as well as static pattern recognition. Audition likely utilizes a similar hierarchy. Olfaction may use something more like a Hopfield attractor neural network, as described in Chapter 13. The networks corresponding to different sense modalities have multiple cross-linkages, more a

mpo- rary philosophers Daniel Dennett [Den91] and Douglas Hofstadter [Hof79, Hof96], in Benjamin Whorf’s [W

e eee eee 255 13.4 Knowledge Representation via Attractor Neural Networks ................... 256 HOUSE_OVERSIGHT_012913 xviii Contents 13.4.1 The Hopfield neural net model ..............0..0 022 e eee 256 13.4.2 Knowledge Representation via Cell Assemblies .................2.05- 257 13.5 Neural Foundati

tive pattern recognition as well as static pattern recognition. Audition likely utilizes a similar hierarchy. Olfaction may use something more like a Hopfield attractor neural network, as described in Chapter 13. The networks corresponding to different sense modalities have multiple cross-linkages, more at

ble movements. Following a metaphor suggested by Douglas Hofstadter MOSES learning covers both "knob twid

FTA00623877 102 5 A Generic Architecture of Human-Like Cognition touch and smell (the latter being better modeled as something like an asymmetric Hopfield net, prone to frequent chaotic dynamics ILIAV*051) - these may also cross-connect with each other and with the more hierarchical perceptual subnetw

ible movements. Following a metaphor suggested by Douglas Hofstadter [Hof96], MOSES learning covers both “k

RSIGHT_013017 102 5 A Generic Architecture of Human-Like Cognition touch and smell (the latter being better modeled as something like an asymmetric Hopfield net, prone to frequent chaotic dynamics [LLW~05]) — these may also cross-connect with each other and with the more hierarchical perceptual subnetwork