Probabilistic Quantifier Logic for General Intelligence
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1 year ago
Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Networks)
logical inference engine, which is a key component of the Novamente Cognition Engine (NCE), an integrative AGI system. Previous papers have discussed the use of indefinite probabilities in the context of a variety of logical inference rules, but have omitted discussion of quantification. Here, in this presentation by Matthew Ikle on the paper by the speaker and Ben Goertzel, delivered at the AGI-08 Conference on Artificial General Intelligence, this gap is filled. A mathematical procedure is provided allowing the propagation of indefinite
probabilities through universal and existential quantifiers, and also through a variety of fuzzy quantifiers corresponding to natural language quantifiers (such as “few”, “man”, “a lot”, “hardly any”, etc.).Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Netwo...all »Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Networks)
logical inference engine, which is a key component of the Novamente Cognition Engine (NCE), an integrative AGI system. Previous papers have discussed the use of indefinite probabilities in the context of a variety of logical inference rules, but have omitted discussion of quantification. Here, in this presentation by Matthew Ikle on the paper by the speaker and Ben Goertzel, delivered at the AGI-08 Conference on Artificial General Intelligence, this gap is filled. A mathematical procedure is provided allowing the propagation of indefinite
probabilities through universal and existential quantifiers, and also through a variety of fuzzy quantifiers corresponding to natural language quantifiers (such as “few”, “man”, “a lot”, “hardly any”, etc.).«
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