Epstein Secrets

ial Intel- ligence, 54(1-2):199 - 227, 1992. PLI2. Jeremy Fishel and Gerald Loeb. Bayesian exploration for intelligent identification of textures. Frontiers in Neurorobotics 6-4, 2012. Pri98. Roy. FYieden. Physics from Fisher Information. Cambridge U. Press, 1998. PT02. G. Pauconnier and M. Turner. Th

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

-14, 1995. HC08. David Hart and Ben Goertzel. Opencog: A software framework for integrative artificial general intelligence. In ACI, volume 171 of Frontiers in Artificial Intelligence and Applications. pages 468-472. IOS Press, 2008. HHPO12. Adam Hampshire, Roger Highfield, Beth Parkin, and Adrian Owen

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

I-14, 1995. HGO8. David Hart and Ben Goertzel. Opencog: A software framework for integrative artificial general intelligence. In AGI, volume 171 of Frontiers in Artificial Intelligence and Applications, pages 468-472. IOS Press, 2008. HHPO12. Adam Hampshire, Roger Highfield, Beth Parkin, and Adrian Owen.

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