Algorithmic Probability and Friends. Bayesian Prediction and by David L. Dowe (auth.), David L. Dowe (eds.) PDF

By David L. Dowe (auth.), David L. Dowe (eds.)

ISBN-10: 3642449573

ISBN-13: 9783642449574

ISBN-10: 3642449581

ISBN-13: 9783642449581

Algorithmic likelihood and buddies: lawsuits of the Ray Solomonoff eighty fifth memorial convention is a suite of unique paintings and surveys. The Solomonoff eighty fifth memorial convention used to be held at Monash University's Clayton campus in Melbourne, Australia as a tribute to pioneer, Ray Solomonoff (1926-2009), honouring his a variety of pioneering works - so much rather, his progressive perception within the early Nineteen Sixties that the universality of common Turing Machines (UTMs) might be used for common Bayesian prediction and synthetic intelligence (machine learning). This paintings maintains to more and more effect and under-pin facts, econometrics, computing device studying, info mining, inductive inference, seek algorithms, information compression, theories of (general) intelligence and philosophy of technology - and functions of those parts. Ray not just predicted this because the route to actual man made intelligence, but additionally, nonetheless within the Sixties, expected levels of growth in computing device intelligence which might finally result in machines surpassing human intelligence. Ray warned of the necessity to expect and talk about the aptitude results - and risks - faster instead of later. almost certainly foremostly, Ray Solomonoff was once an exceptional, satisfied, frugal and adventurous person of light unravel who controlled to fund himself whereas electing to behavior lots of his paradigm-changing study open air of the collage method. the amount comprises 35 papers bearing on the abovementioned subject matters in tribute to Ray Solomonoff and his legacy.

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Extra resources for Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence: Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30 – December 2, 2011

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LNCS (LNAI), vol. 7070, pp. 299–305. Springer, Heidelberg (2013) 97. : Causal discovery of dynamic Bayesian networks. , Zhang, D. ) AI 2012. LNCS, vol. 7691, pp. 902–913. Springer, Heidelberg (2012) 98. : Toward an algorithmic metaphysics. L. ) Solomonoff Festschrift. LNCS (LNAI), vol. 7070, pp. 306–317. Springer, Heidelberg (2013) 99. : Generalized Kraft inequality and arithmetic coding. IBM J. Res. Develop. 20(3), 198–203 (1976) 100. : Modeling by shortest data description. Automatica 14, 465–471 (1978) 101.

L. Dowe 70. : Evaluating a reinforcement learning algorithm with a general intelligence test. A. ) CAEPIA 2011. LNCS, vol. 7023, pp. 1–11. Springer, Heidelberg (2011) 71. : Complexity measures for meta-learning and their optimality. L. ) Solomonoff Festschrift. LNCS (LNAI), vol. 7070, pp. 198–210. Springer, Heidelberg (2013) 72. : An invariant form for the prior probability in estimation problems. Proc. of the Royal Soc. of London A 186, 453–454 (1946) 73. : An introduction to arithmetic coding.

Springer, Heidelberg (2013) 54. : A critical survey of some competing accounts of concrete digital computation. L. ) Solomonoff Festschrift. LNCS (LNAI), vol. 7070, pp. 155–173. Springer, Heidelberg (2013) 55. : Rational decisions. J. Roy. Statist. Soc. (B) 14(1), 107–114 (1952) 56. : Speculations concerning the first ultraintelligent machine. Advances in Computers 6, 31–88 (1965) 57. : Further reflections on the timescale of AI. L. ) Solomonoff Festschrift. LNCS (LNAI), vol. 7070, pp. 174–183. Springer, Heidelberg (2013) 58.

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Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence: Papers from the Ray Solomonoff 85th Memorial Conference, Melbourne, VIC, Australia, November 30 – December 2, 2011 by David L. Dowe (auth.), David L. Dowe (eds.)


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