Epstein Secrets

Perspective on Development. MIT Press, 1997. Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. PF92. Christian Freksa and Robert Milton. Temporal reasoning based on semi-intervals. Artificial Intel- ligence, 54(1-2):199 - 227, 1992

ergoals like gaining knowledge are not funded as much with STI currency just now, as they are not immediately relevant. Action selection, based on ImplicationLinks derived via PLN (between various possible activ- ities and the subgoal S) causes it to start experimentally building some blocks structures. Past ex

Press, 1997. EFTA00624120 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991.

or of Link2Atom. However, the ideas embodied in these rules may be useful; if cleaned up the rules might profitably be ported into the Atomspace as ImplicationLinks. • Representation Building: A stage within MOSES, wherein a candidate Combo program tree (within a deme) is modified by replacing one or more tree

, 1997. HOUSE_OVERSIGHT_013260 References 345 Ede93. Gerald Edelman. Neural darwinism: Selection and reentrant signaling in higher brain function. Neuron, 10, 1993. Elm91. J. Elman. Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7:195-226, 1991. E

intelligent system explicitly represents in its knowledge base, and expends some resources trying to achieve. Goal Nodes (which may be Nodes or, e.g. ImplicationLinks) are used for this purpose in OpenCog. e Goal-Driven Learning: Learning that is driven by the cognitive schematic i.e. by the quest of figuring out