Epstein Secrets

latter situation is disallowed on the software level, and is assumed in discussions not to occur. Sonic Atoms have natural names. For instance. the Schemallode corresponding to the ele- mentary schema function + may quite naturally be named "+". The NumberNode corresponding to the number .5 may naturally be

hat ExecutionLink X A B ExecutionLink2 A B means: X so that ExecutionLink A X B ExecutionLink3 A B means: X so that ExecutionLink A B X Finally, a Schemallode may be associated with a structure called a Graph. Where S is a Schemallode, Graph(S) (x,y): ExecutionLink S x y ) Sometimes, the graph of a Sche

han using a Handle based notation which Atoms would be referred to as 1, 3433322, etc.; but sometimes we will use the Handle notation as well. Some ConceptNodes and conceptual PredicateNode or Schemallodes may correspond with human-language words or phrases like cat, bite, and so forth. This will be the mino

scribed earlier. When an Atom is encountered, it looks into the AtomTable to evaluate the object. In the case that a Schema refers to an ungrounded Schemallode (that is not defined by a ComboTree as defined in Chapter 19), and an appropriate EvaluationLink value isn't in the AtomTable, there's an evaluatio

MemberLinks. This is in accordance with the notion of glocal memory, in the language of which the HPAN attractors are the maps and the corresponding ConceptNodes are the keys. Put simply, when a HPAN attractor is recognized, MemberLinks are created between the HPAN nodes comprising the main body of the attra

On the other hand, given a ConceptNode C involved in inferred ExecutionLinks of the form ExecutionLink C Ai Bi i-1, .. ,n one may wish to find a Schemallode so that the corresponding Schemallode will fulfill this same set of ExecutionLinks. It may seem surprising at first that a ConceptNode might be inv

y, there may be patterns across large numbers of nodes that merit encapsulation in individual nodes. For instance, if there are 1000 fairly similar ConceptNodes, it may be better not to merge them all together, but rather to create a single node to which they all link, reifying the category that they collect

by the quest of figuring out which procedures can be expected to achieve a certain goal in a certain sort of context. • Grounded Schemallode: See Schemallode, Grounded. • Hebbian Learning: An aspect of Attention Allocation, centered on creating and updating HebbianLinks, which represent the simultaneous

at contains all required packages and tools to test and develop OpenCog. • Concept Creation: A general term for cognitive processes that create new ConceptNodes, PredicateNodes or concept maps representing new concepts. • Conceptual Blending: A process of creating new concepts via judiciously combining pie

plementation, the system can still reason about its use of different mind dynamics by considering each MindAgent as a virtual Procedure with a real Schemallode attached to it. This can lead to some valuable learning, with the obvious limitation that in this approach the system is thinking about its MindAgen

at contains all required packages and tools to test and develop OpenCog. • Concept Creation: A general term for cognitive processes that create new ConceptNodes, PredicateNodes or concept maps representing new concepts. • Conceptual Blending: A process of creating new concepts via judiciously combining pie