Epstein Secrets

ch one denoting a "sense" of the word. The clusters are defined by the following relationships: 1. ConceptNodes within a cluster have high-strength SimilarityLinks to each other 2. ConceptNodes in different clusters have low-strength (i.e. dissimilarity-denoting) Similar- ityLinks to each other When a word is

current OpenCog NL comprehension pipeline, the RelEx2Frame component uses hand-coded rules to map RelEx output into sets of relationships utilizing FrameNet and other similar semantic resources. This is definitively viewed as a "stopgap" without a role in a human- level AGI system, but it's described her

onents in practical projects, including theme with proto-AGI intentions. The syntax currently used for describing semantic relationships drawn from FrameNet and other sources is exemplified by the example Al_Benefit:Benefitor(give,$varl) The n indicates the data source, where 1 is a number indicating t

licit low-strength SimilarityLinks in the system in these cases, is obviously much cheaper than using them for all cases. We've been talking about SimilarityLinks, but the approach is more broadly applicable. Any symmetric link type can be dealt with about the same way. For instance, it might be useful to kee

e programmed in. In the latter approach, one may use knowledge from statistical corpus analysis, one may use electronic resources like WordNet and FrameNet, and one may use sophisticated, specialized tools like natural language parsers with hand-coded grammars. Rather than trying to emulate the way a h

more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilarityLinks. Fur- thermore, these various link types reinforce each other. PLN control is guided by im

• Fl ame2Atom: A simple system of hand-coded rules for translating the output of RelEx2Frame (logical representation of semantic relationships using FrameNet relationships) into Atoms. • Freezing: Saving Atoms from the in-RAM AtomSpace to disk. • General Intelligence: Often used in an informal, commonsen

ar more large, complex and tangled than even this one. In CogPrime, ECAN enforces heterarchy via building SymmetricHebbianLinks, and PLN by building SimilarityLinks, IntensionalSimilarityLinks and ExtensionalSimilarityLinks. Fur- thermore, these various link types reinforce each other. PLN control is guided by im

e Frame2Atom: A simple system of hand-coded rules for translating the output of RelEx2Frame (logical representation of semantic relationships using FrameNet relationships) into Atoms. e Freezing: Saving Atoms from the in-RAM Atomspace to disk. e General Intelligence: Often used in an informal, commonsen