Titlebook: Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence; Papers from the Ray David L. Dowe Book 2013 Springer

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Design of a Conscious Machineately imitates, unconsciously initiates attention shifts, wonders what if, learns why, and improves from mistakes. We will specify the functional requirements for a few particularly important parts, as connectionist schemas. This poses several problems for established disciplines of AI, to produce c

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No Free Lunch versus Occam’s Razor in Supervised Learningrmation theory to argue the case for a universal bias allowing an algorithm to succeed in all interesting problem domains. Additionally, we give a new algorithm for off-line classification, inspired by Solomonoff induction, with good performance on all structured (compressible) problems under reason

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Algorithmic Probability and Friends. Bayesian Prediction and Artificial IntelligencePapers from the Ray

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Inductive Inference and Partition Exchangeability in Classificationhe presence of infinite amounts of training data, a classifier based on partition exchangeability still continues to benefit from a joint prediction of labels for the whole population of test items. Some remarks about the relation of this work to generic convergence results in predictive inference a