Epstein Secrets

utable AtomHandles as compactly as possible, while still enabling very efficient modification of the mutable properties of an Atom (TruthValues and AttentionValues). • Perform queries as fast as possible. • Keep the working set of all Atoms currently being used by CogPrime's cognitive dynamics in RAM. • Save

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,

ImportanceUpdating MindAgent must compute interaction-channel importance separately from ordinary importance. And, just as we have channel-specific AttentionValues, we may also have channel-specific TruthValues. This allows the system to separately account for the frequency of a given percep- tual item in a giv

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

will fail because there is nothing to study! These same tables may be used in the attention allocation process, for assigning of MindAgent- specific AttentionValues to Atoms. WIKISOURCE:MapMining 42.4 Mining the AtomSpace for Maps Searching for general maps in a complex AtomSpace is an unrealistically difficult

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