Epstein Secrets

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con

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

ed to reach a more orthogonal set. A straightfor- ward way to do this is to exploit the reduction to nor

resent is carried out, either by - PLN inference within OpenCog, drawing the conclusion that a block is present from the exported predicates, using ImplicationLinks comprising a working definition of a "block" - A predicate comprising the definition of "block", previously imported into DeSTIN from OpenCog and

s for example, the words "sing" and "apologize" are both verbs, and thus share some linguistic structure, but one cannot say "I apologized a song to Vicky"; if these two verbs were initially grouped together into a common lexical entry, they must later be split apart. - The definition of a good lexic

of the Syn2Sem approach mentioned above into a reverse-order. Sem2Syn system for language generation. Given that the Syn2Sem rules are expressed as ImplicationLinks, they can be reversed auto- matically and immediately - although, the reversed versions will not necessarily have the same truth values. So if a col

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con

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

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concr

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