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, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. • CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer c
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
, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. • CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer c
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
hing, by having another agent explicitly guide it in doing the thing. For instance, teaching a dog to sit by pushing its butt to the ground. CSDLN: (Compositional Spatiotemporal Deep Learning Network): A hierarchical pattern recognition network, in which each layer corresponds to a certain spatiotemporal granularity, the nodes on a given layer cor
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
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