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s, and a richer methodology for producing outputs. These are all not only HPANs but have a more particular structure that in Chapter 27 is called a Compositional Spatiotemporal Deep Learning Network or CSDLN. The particulars of the use of HPANs with OpenCog are perhaps best explained via enumer- ation of memory types and control operations. EFT
tion of DeSTIN and OpenCog involves two key aspects: • recognition of patterns in sets of DeSTIN states, and exportation of these patterns into the OpenCog Atomspace EFTA00624321 29.3 Integrating DeSTIN and OpenCog 175 • use of OpenCog-created concepts within DeSTIN nodes, alongside statistically-derived "cen
, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. • CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer c
types of artificial money, STICurrency and LTICur- rency. Theoretically these may be converted to one another. • Attentional Focus: The Atoms in an OpenCog Atomspace whose ShortTennImportance values lie above a critical threshold (the AttentionalFocus Boundary). The Attention Allo- cation subsystem treats these A
, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. • CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer c
types of artificial money, STICurrency and LTICur- rency. Theoretically these may be converted to one another. • Attentional Focus: The Atoms in an OpenCog Atomspace whose ShortTennImportance values lie above a critical threshold (the AttentionalFocus Boundary). The Attention Allo- cation subsystem treats these A
hing, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer cor
nt types of artificial money, STICurrency and LTICur- rency. Theoretically these may be converted to one another. Attentional Focus: The Atoms in an OpenCog Atomspace whose ShortTermImportance values lie above a critical threshold (the AttentionalFocus Boundary). The Attention Allo- cation subsystem treats these At
Entities connected to both Compositional Spatiotemporal Deep Learning Network and OpenCog Atomspace
ConceptNodes
ORGANIZATIONOpenCog
ORGANIZATION
Marc Rich
PERSONImplicationLinks
ORGANIZATIONMindAgents
PERSONTruthValues
ORGANIZATIONDeSTIN
ORGANIZATION
Stephen Hawking
PERSONPredicateNodes
ORGANIZATIONSTICurrency
LOCATIONCogServer
ORGANIZATIONScheduler
ORGANIZATION
Dorner
ORGANIZATIONCogPrime
ORGANIZATION
Ray Kurzweil
PERSONPredicateNode
LOCATION
Vicky Ward
PERSON
Rui Liu
PERSON
Joscha Bach
PERSONSimilarityLinks
ORGANIZATION