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e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con
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
ed to reach a more orthogonal set. A straightfor- ward way to do this is to exploit the reduction to nor
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
e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con
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
e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concr
n concepts in one of Douglas Hofstadter’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 ExtensionalSimilari
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