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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
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 involved with ExecutionLinks, but remember that a function can be seen as a set of tupl
possible predicate whose corresponding PredicateNode P satisfies SatisfyingSet(P) C 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
entioned: 1. Via preprocessing of perceptual inputs (e.g. the names of NumberNode, CharacterNodes) 2. Via hard-wiring of names for Schemallodes and PredicateNodes corresponding to built-in elementary schema (e.g. +, AND, Say) If an Atom A has a name n in the system, we may write A.name n On the other hand,
ages in terms of memory usage and lookup speed. For purposes of logically reasoning about schema, it is useful to create binary links repre- senting ExecutionLinks with some of their arguments fixed. We name these as follows: ExecutionLink) A B means: X so that ExecutionLink X A B ExecutionLink2 A B means: X s
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
maPool. 24.6 GoalBasedSchemaLearning Finally, we have the process of trying to figure out how to achieve goals, i.e. trying to learn links between ExecutionLinks and goals G. This process should he focused on goals that have a high importance but for which feasible achievement-methodologies are not yet known.
Entities connected to both PredicateNodes and ExecutionLinks
OpenCog
ORGANIZATIONConceptNodes
ORGANIZATIONPredicateNode
LOCATION
Marc Rich
PERSONMindAgents
PERSONTruthValues
ORGANIZATIONImplicationLinks
ORGANIZATIONCogPrime
ORGANIZATIONDeSTIN
ORGANIZATIONCombo
LOCATIONSchemallode
PERSONSTICurrency
LOCATION
Marvin Minsky
PERSONScheduler
ORGANIZATIONthe Webmind AI Engine
ORGANIZATIONAttentionValues
ORGANIZATIONSchemata
ORGANIZATIONOpenSim
ORGANIZATIONSimilarityLinks
ORGANIZATIONFishgram
PERSON