Probabilistic Quantifier Logic for General Intelligence: An Indefinite Probabilities Approach

: 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 this gap is filled, and 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.). Proper probabilistic handling of various quantifier transformation rules is also discussed. Together with the ideas in prior publications, and a forthcoming sequel paper on indefinite probabilities for intension...

• Type: Conference
• Year: 2008
• Where: AGI
• Authors: Matthew Iklé, Ben Goertzel
• Keywords: AGI 2008, Artificial Intelligence, Fuzzy Quantifiers, Indefinite Probabilities, Quantifiers