Epstein Secrets

links (such as SimilarityLinks) • adding "Hebbian weights" to other links (such as SimilarityLinks) • implicitly interpreting other links (such as SimilarityLinks) as HebbianLinks Further, these strategies may potentially be used together. There are some obvious semantic relationships to be used in interpreti

routines supplied to it by an external source (e.g. another AI system such as OpenCog) 2. Utilizing one of OpenCogPrime's cognitive processes (the "Fishgram" frequent subhyper- graph mining algorithm) to recognize patterns in sets of DeSTIN states, and then recording these patterns in OpenCogPrime's Atom

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

a greedy search, so it can quickly find many patterns. In contrast, algorithms like MOSES are designed to find a small number of the best patterns. Fishgram works by finding a set of objects that have links in common, so it will be most effective if the AtomSpace has a lot of raw data, with simple patter

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

rations) Extension: In PLN, the extension of a node refers to the instances of the category that the node represents. In contrast is the intension. Fishgram (Frequent and Interesting Sub-hypergraph Mining): A pattern mining algorithm for identifying frequent and/or interesting sub-hypergraphs in the Atoms