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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
FTA00624680 534 A Glossary Sch06. .1. Schmidhuber. Code! machines: Fully Self-referential Optimal Universal Self-improvers. In B. Go- ertzel and C. Pennachin, editors, Artificial General Intelligence, pages 119-226. 2006. SDCCK08a. Steven Schockaert, Martine De Cock. Chris Cornelis, and Etienne E. Kerne.
, 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
EFTA00624125 350 A Glossary Sch06. J. Schmidhuber. Godel machines: Ashy Self-referential Optimal Universal Self-improvers. In B. Goertzel and C. Pennachin, editors, Artificial General Intelligence, pages 119-226. 2006. Sch07. Dale Schunk. Theories of Learning: An Educational Perspective. Prentice Hall
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
_OVERSIGHT_013265 350 A Glossary Sch06. J. Schmidhuber. Godel machines: Fully Self-referential Optimal Universal Self-improvers. In B. Goertzel and C. Pennachin, editors, Artificial General Intelligence, pages 119-226. 2006. SchO7. Dale Schunk. Theories of Learning: An Educational Perspective. Prentice Hall,
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