Bayesian Probability

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Bayesian Probability

A revision of a previous probability based on new information. In Bayesian analysis, one makes mathematical assumptions about unavailable information. As that information is gathered and disseminated, the Bayesian probability corrects or replaces the assumptions and alters its results accordingly.
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Other notable signees for the letter include Mustafa Suleyman, founder at the Google-acquired startup DeepMind, Element AI's (http://ibtimes.com/canadian-artificial-intelligence-company-element-ai-receives-102m-funding-2552369) Yoshua Bengio and Bayesian Logic founder Stuart Russell.
Sangero bases his thesis on empirical studies (which supposedly prove the large prevalence of false confessions as a major cause for false convictions and the fact-finders' inability to discern true from false confessions) and on a Bayesian logic analysis.
As an alternative, we investigate a model in which members might defer to an emerging consensus, even when that consensus choice might conflict with an individual's Bayesian logic. Neither model is supported by the data.
It's clearly an easier route than trying to explain Bayesian logic!
Acquiring knowledge is an important stage in creating expert systems: it is achieved by the knowledge engineer who needs to have a good knowledge of the methods of representing knowledge, methods provided by knowledge engineering such as: the method based on production rules; the method based on semantic nets; the frame-based method; the method based on logical models (propositional logic, the logic of predicates of the 2nd order); the method based on probabilistic logic (Bayesian logic); the method based on fuzzy set and logic (Moise, 2007).
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