Epstein Secrets

ts subgoals, or spend on executing procedures) These various processes are carried out in a manner orchestrated by Domer's Psi model as refined by Joscha Bach (as reviewed in Chapter 4 above), which supplies (among other features) • a specific theory regarding what "demands" should be used to spawn the top

latter situation is disallowed on the software level, and is assumed in discussions not to occur. Sonic Atoms have natural names. For instance. the Schemallode corresponding to the ele- mentary schema function + may quite naturally be named "+". The NumberNode corresponding to the number .5 may naturally be

hat ExecutionLink X A B ExecutionLink2 A B means: X so that ExecutionLink A X B ExecutionLink3 A B means: X so that ExecutionLink A B X Finally, a Schemallode may be associated with a structure called a Graph. Where S is a Schemallode, Graph(S) (x,y): ExecutionLink S x y ) Sometimes, the graph of a Sche

ocedure Node: A Schemallode or PredicateNode • Psi: A model of motivated action and emotion, originated by Dietrich Dorner and further developed by Joscha Bach, who incorporated it in his proto-AGI system MicroPsi. OpenCog- Prime's motivated-action component, OpenPsi, is roughly based on the Psi model. • Ps

by the quest of figuring out which procedures can be expected to achieve a certain goal in a certain sort of context. • Grounded Schemallode: See Schemallode, Grounded. • Hebbian Learning: An aspect of Attention Allocation, centered on creating and updating HebbianLinks, which represent the simultaneous

ocedure Node: A Schemallode or PredicateNode • Psi: A model of motivated action and emotion, originated by Dietrich Dorner and further developed by Joscha Bach, who incorporated it in his proto-AGI system MicroPsi. OpenCog- Prime's motivated-action component, OpenPsi, is roughly based on the Psi model. • Ps

plementation, the system can still reason about its use of different mind dynamics by considering each MindAgent as a virtual Procedure with a real Schemallode attached to it. This can lead to some valuable learning, with the obvious limitation that in this approach the system is thinking about its MindAgen