Epstein Secrets

n-channel importance separately from ordinary importance. And, just as we have channel-specific AttentionValues, we may also have channel-specific TruthValues. This allows the system to separately account for the frequency of a given percep- tual item in a given interaction channel. However, no specific mec

hema execution in the first place. The problem of credit assignment thus becomes a problem of creating appropriate heuristics to guide inference of ImplicationLinks of the form described above. Assignment of credit is then implicit in the calculation of truth values for these links. The difficulty is that the pr

FTA00624489 41.5 Inference-Cuided Evolution of Pattern-Embodying Predicates 343 components. We want to identify and reward those Predicates whose TruthValues actually add information beyond what is implicit in the simple fact of combining their components. For instance, consider the PredicateNode AND I

ms an action and achieves a goal. There is code to create implications based on these conjunctions. After finding many conjunctions, it can produce ImplicationLinks based on some of them. Here is an example where the Al-controlled virtual robot discovers how to get energy. (ImplicationLink (AndLink (Evaluatio

largely by ECAN acting on Atten- tionValues and HebbianLinks in the Atomspace: whereas declarative knowledge is dealt with largely by PLN acting on TruthValues and logical links, also in the AtomSpace). So one has a mix of the "different representations for different memory types" approach and the "differen

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

lso refers to an Atom that is used as the first argument of a ContextLink. The second argument of the ContextLink then contains Links or Nodes, with TruthValues calculated restricted to the context defined by the first argument. For instance, (ContextLink USA (InheritanceLink person obese )). • Core: The M

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

lso refers to an Atom that is used as the first argument of a ContextLink. The second argument of the ContextLink then contains Links or Nodes, with TruthValues calculated restricted to the context defined by the first argument. For instance, (ContextLink USA (InheritanceLink person obese )). • Core: The M

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

also refers to an Atom that is used as the first argument of a ContextLink. The second argument of the ContextLink then contains Links or Nodes, with TruthValues calculated restricted to the context defined by the first argument. For instance, (ContextLink USA (InheritanceLink person obese )). Core: The MindO

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