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the same Atom from different perspectives may be grouped into CompositeTruthValue objects. • Universal Intelligence: A technical term introduced by Shane Legg and Marcus Hutter, describing (roughly speaking) the average capability of a system to carry out computable goals in computable environments, where
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"
the same Atom from different perspectives may be grouped into CompositeTruthValue objects. • Universal Intelligence: A technical term introduced by Shane Legg and Marcus Hutter, describing (roughly speaking) the average capability of a system to carry out computable goals in computable environments, where
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"
the same Atom from different perspectives may be grouped into CompositeTruthValue objects. e Universal Intelligence: A technical term introduced by Shane Legg and Marcus Hutter, describing (roughly speaking) the average capability of a system to carry out computable goals in computable environments, where g
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
Entities connected to both Shane Legg and First-Order
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ORGANIZATIONHebbian Learning
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ORGANIZATIONthe Webmind AI Engine
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