Epstein Secrets

. • 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

Mathias. Optimization using disributed genetic algorithms. In Parallel Problem Solving from Nature, Edited by H Schwefel and R Manner, 1990. 5204. R. Sun and X. Zhang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. Tes59. Lucien TesniEre. Elem

. • 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

2000. SV99. A. J. Storkey and R. Valabregue. The basins of attraction of a new hopfield learning rule. Neural Networks, 12:869-876, 1999. $204. R. Sun and X. 2hang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. TC97. M. Tomasello and .1. C

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

ub, 2000. SV99. A. J. Storkey and R. Valabregue. The basins of attraction of a new hopfield learning rule. Neural Networks, 12:869-876, 1999. SZ04, R. Sun and X. Zhang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. TC97. M. Tomasello and J. Call