Epstein Secrets

exts may be used in schema execution, but they're used only indirectly, via being passed to TruthValueEvaluators used for evaluating truth values of PredicateNodes or Com- poundTermNodes that occur internally in schemata being executed. EFTA00624272 EFTA00624273 Section III Perception and Action EFTA00624

links (such as SimilarityLinks) • adding "Hebbian weights" to other links (such as SimilarityLinks) • implicitly interpreting other links (such as SimilarityLinks) as HebbianLinks Further, these strategies may potentially be used together. There are some obvious semantic relationships to be used in interpreti

subgraphs containing Atom-valued variables . Each such subgraph may be represented as a PredicateNode, and frequent subgraph mining will find such PredicateNodes that have surprisingly high truth values when evaluated across the Atomspace. But unlike MOSES when applied as described above, such an algorithm wi

licit low-strength SimilarityLinks in the system in these cases, is obviously much cheaper than using them for all cases. We've been talking about SimilarityLinks, but the approach is more broadly applicable. Any symmetric link type can be dealt with about the same way. For instance, it might be useful to kee

. • Imitation Learning: Learning via copying what some other agent is observed to do. • Implication: Often refers to an ImplicationLink between two PredicateNodes, indicating an (extensional, intensional or mixed) logical implication. • Implicit Knowledge Representation: Representation of knowledge via having

more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilarityLinks. Fur- thermore, these various link types reinforce each other. PLN control is guided by im

er atoms. Grounded- PredicateNodes and GroundedSchemaNodes connect to explicitly represented procedures (sometimes in the Combo language); ungrounded PredicateNodes and SchemaNodes are abstract and, like ConceptNodes, purely characterized by their relationships. Node Probability: Many PLN inference rules rely on

ar more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilarityLinks. Fur- thermore, these various link types reinforce each other. PLN control is guided by im