Epstein Secrets

ous levels of abstraction. The prominence of visual and other sensory metaphors in abstract cognition is well known lArn69, Gar00]; and according to Lakoff and Nunez 1LN001 even pure mathematics is grounded in physical perception and action in very concrete ways. We begin by discussing the perception a

some of the properties that the above ECAN equations display when we use an ECAN defined by them as an associative memory network in the manner of a Hopfield network. We consider a situation where the ECAN is supplied with memories via a "training" phase in which one imprints it with a series of binary

orks Economic Attention Networks (ECANs) are dynamical systems based on the propagation of STI and LTI values. They are similar in many respects to Hopfield nets, but are based on a different conceptual foundation involving the propagation of amounts of (conserved) currency rather than neural-net activa

that one sees in some precivilized cultures. But in other cases this kind of analogy leads to robust sorts of reasoning - for instance, in reading Lakoff and Nunez's ILN00] intriguing explorations of the cognitive foundations of mathematics, it is pretty easy to see that most of the metaphors on which

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

ts that one sees in some precivilized cultures. But in other cases this kind of analogy leads to robust sorts of reasoning - for instance, in reading Lakoff and Nunez’s [LN00] intriguing explorations of the cognitive foundations of mathematics, it is pretty easy to see that most of the metaphors on which

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