Epstein Secrets

, among them the explicit use of a ConceptBlending MindAgent, that blends two or more ConceptNodes into a new one. • Confidence: A component of an OpenCog/PLN TruthValue, which is a scaling into the interval 10,11 of the weight of evidence associated with a truth value. In the simplest case (of a probabilistic Simpl

nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"

, among them the explicit use of a ConceptBlending MindAgent, that blends two or more ConceptNodes into a new one. • Confidence: A component of an OpenCog/PLN TruthValue, which is a scaling into the interval 10,11 of the weight of evidence associated with a truth value. In the simplest case (of a probabilistic Simpl

nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"

ys, among them the explicit use of a ConceptBlending MindAgent, that blends two or more ConceptNodes into a new one. e Confidence: A component of an OpenCog/PLN TruthValue, which is a scaling into the interval [0,1] of the weight of evidence associated with a truth value. In the simplest case (of a probabilistic Simple

et and seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. PLN: short for Probabilistic Logic Networks PLN, First-Order: See First-Order Inference PLN, Higher-Order: See Higher-Order Inference PLN Rules: A PLN Rule takes as input one or more Atoms (the “premises”, us