Epstein Secrets

cedure Learning as Program Learning 30.1 Introduction Broadly speaking, the learning of predicates and schemata (executable procedures) is done in CogPrime via a number of different methods, including for example PLN inference and concept predicatization (to be discussed in later chapters). Most of thes

PLN Rules as GroundedSchemallodes PLN inference rules may be represented as GroundedSchemallodes. So for instance the PLN Deduction Rule, becomes a GroundedSchemallode with the properties: • Input: a pair of links (LI, L2), where LI and L2 are the same type, and must be one of InheritanceLink, ImplicationLink, Sub

49.6 Cognitive Processes 481 CogPrime's multi-memory design, it's natural to consider CogPrime's cognitive processes in terms of which memory subsystems they focus on (although, this is

get processor time, at which point in time. • Schema: A "script" describing a process to be carried out. This may be explicit, as in the case of a GroundedSchemallode, or implicit, as the case in Schema maps or ungrounded Schemallodes. • Schema Encapsulation: The process of automatically recognizing a Schema Map

concepts in one of Douglas HoEstadter's books. Naturally, real concept heterarchies are far more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilar

get processor time, at which point in time. • Schema: A "script" describing a process to be carried out. This may be explicit, as in the case of a GroundedSchemallode, or implicit, as the case in Schema maps or ungrounded Schemallodes. • Schema Encapsulation: The process of automatically recognizing a Schema Map