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  1. Uncharted Aspects of Human Intelligence in Knowledge-Based “Intelligent” Systems.Ronaldo Vigo, Derek E. Zeigler & Jay Wimsatt - 2022 - Philosophies 7 (3):46.
    This paper briefly surveys several prominent modeling approaches to knowledge-based intelligent systems design and, especially, expert systems and the breakthroughs that have most broadened and improved their applications. We argue that the implementation of technology that aims to emulate rudimentary aspects of human intelligence has enhanced KBIS design, but that weaknesses remain that could be addressed with existing research in cognitive science. For example, we propose that systems based on representational plasticity, functional dynamism, domain specificity, creativity, and concept learning, with (...)
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  • Coherent Probability From Incoherent Judgment.Daniel Osherson, David Lane, Peter Hartley & Richard R. Batsell - 2001 - Journal of Experimental Psychology: Applied 7 (1):3.
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  • The Metaphysical Character of the Criticisms Raised Against the Use of Probability for Dealing with Uncertainty in Artificial Intelligence.Carlotta Piscopo & Mauro Birattari - 2008 - Minds and Machines 18 (2):273-288.
    In artificial intelligence (AI), a number of criticisms were raised against the use of probability for dealing with uncertainty. All these criticisms, except what in this article we call the non-adequacy claim, have been eventually confuted. The non-adequacy claim is an exception because, unlike the other criticisms, it is exquisitely philosophical and, possibly for this reason, it was not discussed in the technical literature. A lack of clarity and understanding of this claim had a major impact on AI. Indeed, mostly (...)
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  • Aggregating Disparate Estimates of Chance.Daniel Osherson - manuscript
    We consider a panel of experts asked to assign probabilities to events, both logically simple and complex. The events evaluated by different experts are based on overlapping sets of variables but may otherwise be distinct. The union of all the judgments will likely be probabilistic incoherent. We address the problem of revising the probability estimates of the panel so as to produce a coherent set that best represents the group’s expertise.
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  • Linguistic Quantifiers Modeled by Sugeno Integrals.Mingsheng Ying - 2006 - Artificial Intelligence 170 (6-7):581-606.
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  • Quasi-Bayesian Analysis Using Imprecise Probability Assessments And The Generalized Bayes' Rule.Kathleen M. Whitcomb - 2005 - Theory and Decision 58 (2):209-238.
    The generalized Bayes’ rule (GBR) can be used to conduct ‘quasi-Bayesian’ analyses when prior beliefs are represented by imprecise probability models. We describe a procedure for deriving coherent imprecise probability models when the event space consists of a finite set of mutually exclusive and exhaustive events. The procedure is based on Walley’s theory of upper and lower prevision and employs simple linear programming models. We then describe how these models can be updated using Cozman’s linear programming formulation of the GBR. (...)
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  • Evaluation of the Plausibility of a Conclusion Derivable From Several Arguments with Uncertain Premises.Christian George - 1999 - Thinking and Reasoning 5 (3):245 – 281.
    Previous studies with adult participants have investigated reasoning from one or two uncertain premises with simple deductive arguments. Three exploratory experiments were designed to extend these results by investigating the evaluation of the plausibility of the conclusion of "combined" arguments, i.e. arguments constituted by two or more "atomic" standard arguments which each involved the same conclusion and one uncertain premise out of two. One example is "If she meets Nicolas it is very improbable she will go to the swimming pool; (...)
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