Books on the topic 'Algorithmic probability theory'

Neuts, Marcel F. Algorithmic probability: A collection of problems. London: Chapman & Hall, 1995.

Calude, Cristian. Information and Randomness: An Algorithmic Perspective. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994.

Universal artificial intelligence: Sequential decisions based on algorithmic probability. Berlin: Springer, 2005.

Nonlinear discrete optimization: An algorithmic theory. Zürich, Switzerland: European Mathematical Society Publishing House, 2010.

Habib, Michel. Probabilistic Methods for Algorithmic Discrete Mathematics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998.

author, Sarich Marco 1985, ed. Metastability and Markov state models in molecular dynamics: Modeling, analysis, algorithmic approaches. Providence, Rhode Island: American Mathematical Society, 2013.

Dubhashi, Devdatt. Concentration of measure for the analysis of randomized algorithms. Cambridge: Cambridge University Press, 2012.

Scheduling: Theory, Algorithms, and Systems. New York, NY: Springer New York, 2008.

service), SpringerLink (Online, ed. Scheduling: Theory, Algorithms, and Systems. 4th ed. Boston, MA: Springer US, 2012.

Concentration of measure for the analysis of randomized algorithms. Cambridge: Cambridge University Press, 2009.

Ching, Wai-Ki. Markov Chains: Models, Algorithms and Applications. 2nd ed. Boston, MA: Springer US, 2013.

Benveniste, Albert. Adaptive Algorithms and Stochastic Approximations. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990.

Duflo, Marie. Random Iterative Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997.

Probability and random processes: Theory and signal processing applications. Hoboken, NJ: Wiley, 2012.

Chang, Hyeong Soo. Simulation-Based Algorithms for Markov Decision Processes. 2nd ed. London: Springer London, 2013.

Cyganowski, Sasha. From Elementary Probability to Stochastic Differential Equations with MAPLE®. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.

Random trees: An interplay between combinatorics and probability. New York: Springer, 2009.

Sinclair, Alistair. Algorithms for Random Generation and Counting: A Markov Chain Approach. Boston, MA: Birkhäuser Boston, 1993.

Neapolitan, Richard E. Probabilistic reasoning in expert systems: Theory and algorithms. New York: Wiley, 1990.

Wei guan xi tong yi chuan suan fa you hua she ji li lun yu ying yong. Beijing Shi: Zhong guo shui li shui dian chu ban she, 2010.

service), SpringerLink (Online, ed. Ubiquitous Quantum Structure: From Psychology to Finance. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

Analysis and algorithms for service parts supply chains. New York: Springer, 2005.

Meyer, Yves. Wavelets: Algorithms & applications. Philadelphia: Society for Industrial and Applied Mathematics, 1993.

J, Hu, Hopkins D. A, and Lewis Research Center, eds. An overview of engineering concepts and current design algorithms for probabilistic structural analysis. Cleveland, Ohio: NASA Lewis Research Center, 1995.

1942-, Jørgensen Steffen, Quincampoix Marc, and Vincent Thomas L, eds. Advances in dynamic game theory: Numerical methods, algorithms and applications to ecology and economics. Boston: Birkhäuser, 2007.

SAGA 2009 (2009 Sapporo, Japan). Stochastic algorithms: Foundations and applications : 5th international symposium, SAGA 2009 Sapporo, Japan, October 26-28, 2009 : proceedings. Berlin: Springer, 2009.

First course on fuzzy theory and applications. Berlin: Springer-Verlag, 2005.

1956-, Watanabe Michiko, and Yamaguchi Kazunori 1962-, eds. The EM algorithm and related statistical models. New York: Marcel Dekker, 2004.

Ensemble methods: Foundations and algorithms. Boca Raton, FL: Taylor & Francis, 2012.

Balsamo, Simonetta. Analysis of Queueing Networks with Blocking. Boston, MA: Springer US, 2001.

System identification with quantized observations. Boston: Birkhäuser, 2010.

Alonso, Laurent. Random Generation of Trees: Random Generators in Computer Science. Boston, MA: Springer US, 1995.

Dowe, David L. Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence. Springer, 2013.

Kolmogorov Complexity and Algorithmic Randomness. American Mathematical Society, 2017.

Hutter, Marcus. Universal Artificial Intelligence: Sequential Decisions Based On Algorithmic Probability. Springer, 2004.

Hutter, Marcus. Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability. Springer Berlin / Heidelberg, 2010.

Algorithmic Probability And Combinatorics Ams Special Sessions On Algorithmic Probability And Combinatorics October 56 2007 Depaul University Chicago Illinois Ams Special Session October 45 2008 University Of British Columbia Vancouver Bc Canada. American Mathematical Society(RI), 2010.

Eagle, Antony. Probability and Randomness. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.22.

Algorithmic Game Theory: 5th International Symposium, SAGT 2012, Barcelona, Spain, October 22-23, 2012. Proceedings. Springer London, Limited, 2012.

Serna, Maria. Algorithmic Game Theory: 5th International Symposium, SAGT 2012, Barcelona, Spain, October 22-23, 2012. Proceedings. Springer, 2012.

Dowe, David L. 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. Springer, 2013.

Lavi, Ron. Algorithmic Game Theory: 7th International Symposium, SAGT 2014, Haifa, Israel, September 30 -- October 2, 2014, Proceedings. Springer London, Limited, 2014.

Stochastic Approximation and Recursive Algorithms and Applications. Springer London, Limited, 2013.

Bazaraa, Mokhtar S., C. M. Shetty, and Hanif D. Sherali. Nonlinear Programming: Theory and Algorithms. Wiley & Sons, Incorporated, John, 2013.

Bazaraa, Mokhtar S., C. M. Shetty, and Hanif D. Sherali. Nonlinear Programming: Theory and Algorithms. Wiley & Sons, Limited, John, 2014.

Bazaraa, Mokhtar S., C. M. Shetty, and Hanif D. Sherali. Nonlinear Programming: Theory and Algorithms. Wiley & Sons, Incorporated, John, 2008.

Evans, Diane L., Andrew G. Glen, John H. Drew, and Lawrence M. Leemis. Computational Probability: Algorithms and Applications in the Mathematical Sciences. Springer London, Limited, 2016.

Evans, Diane L., Andrew G. Glen, John H. Drew, and Lawrence M. Leemis. Computational Probability: Algorithms and Applications in the Mathematical Sciences. Springer, 2018.

Evans, Diane L., Andrew G. Glen, John H. Drew, and Lawrence M. Leemis. Computational Probability: Algorithms and Applications in the Mathematical Sciences. Springer International Publishing AG, 2016.

Leemis, Lawrence, Diane L. Evans, Andrew G. Glen, and John H. Drew. Computational Probability: Algorithms and Applications in the Mathematical Sciences. Springer London, Limited, 2008.