@article{journals/corr/abs-0809-2965,
	title = {On Time-Bounded Incompressibility of Compressible Strings},
	author = {Edgar G. Daylight and Wouter M. Koolen and Paul M. B. Vitányi},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0809.html#abs-0809-2965},
	volume = {abs/0809.2965},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2b8bad89cc43610b2310de2b456b084be/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0809.2965}, date = {2008-10-02},
	keywords = {dblp }
}

@article{journals/corr/abs-0809-2754,
	title = {Algorithmic information theory},
	author = {Peter D. Grunwald and Paul M. B. Vitányi},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0809.html#abs-0809-2754},
	volume = {abs/0809.2754},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/283573a93c867e03b5576b0aec3c19452/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0809.2754}, date = {2008-10-02},
	keywords = {dblp }
}

@article{journals/corr/abs-0809-2553,
	title = {Normalized Information Distance},
	author = {Paul M. B. Vitanyi and Frank J. Balbach and Rudi Cilibrasi and Ming Li},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0809.html#abs-0809-2553},
	volume = {abs/0809.2553},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2072779332d189fac1eb394f616d53ca8/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0809.2553}, date = {2008-10-02},
	keywords = {dblp }
}

@article{journals/corr/abs-0809-2546,
	title = {Depth as Randomness Deficiency},
	author = {Luis Antunes and Armando Matos and Andre Souto and Paul M. B. Vitányi},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0809.html#abs-0809-2546},
	volume = {abs/0809.2546},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/20be5d235ee402554da0a2627623df64a/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0809.2546}, date = {2008-10-02},
	keywords = {dblp }
}

@incollection{reference/algo/Vitanyi08,
	title = {Registers.},
	author = {Paul M. B. Vitányi},
	booktitle = {Encyclopedia of Algorithms},
	crossref = {reference/algo/2008},
	editor = {Ming-Yang Kao},
	publisher = {Springer},
	url = {http://dblp.uni-trier.de/db/reference/algo/algo2008.html#Vitanyi08},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/275116174aba9b1f86a00c49a4eea1d49/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1007/978-0-387-30162-4_338}, isbn = {978-0-387-30162-4}, date = {2008-09-17},
	keywords = {dblp }
}

@article{ChaterVitanyi03,
	title = {Simplicity: a unifying principle in cognitive science?},
	author = {N. Chater and P. Vitanyi},
	journal = {Trends in Cognitive Sciences},
	pages = {19-22},
	volume = {7},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/23b1921adb031b2597bd40ee59947a832/brian.mingus},
	description = {CCNLab BibTeX},
	keywords = {cogn }
}

@article{cilibrasi03compression,
	title = {Clustering by compression},
	author = {Rudi Cilibrasi and Paul Vitanyi},
	journal = {IEEE Trans. Information Theory},
	number = {4},
	url = {http://arxiv.org/abs/cs/0312044},
	volume = {51},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/2d608ba59a20b45b47e7089e331310525/msn},
	howpublished_ = {Cornell University}, language = {english},
	keywords = {cites.gradu mrefs research.clustering science.statistics }
}

@article{Vitanyi:2000:DEP,
	title = {A discipline of evolutionary programming},
	author = {Paul Vitanyi},
	journal = {Theoretical Computer Science},
	month = {28 June},
	number = {1--2},
	pages = {3--23},
	url = {http://www.elsevier.nl/gej-ng/10/41/16/175/21/22/article.pdf},
	volume = {241},
	year = {2000},
	biburl = {http://www.bibsonomy.org/bibtex/23c6e75e2c0433cd977a2a9c60c559af4/brazovayeye},
	abstract = {Genetic fitness optimization using small populations
                 or small population updates across generations
                 generally suffers from randomly diverging evolutions.
                 We propose a notion of highly probable fitness
                 optimization through feasible evolutionary computing
                 runs on small size populations. Based on rapidly mixing
                 Markov chains, the approach pertains to most types of
                 evolutionary genetic algorithms, genetic programming
                 and the like. We establish that for systems having
                 associated rapidly mixing Markov chains and appropriate
                 stationary distributions the new method finds optimal
                 programs (individuals) with probability almost 1. To
                 make the method useful would require a structured
                 design methodology where the development of the program
                 and the guarantee of the rapidly mixing property go
                 hand in hand. We analyze a simple example to show that
                 the method is implementable. More significant examples
                 require theoretical advances, for example with respect
                 to the Metropolis filter.},
	issn = {0304-3975}, size = {21 pages}, bibdate = {Tue Oct 31 11:38:29 MST 2000}, notes = {Update of \cite{alt96*67} Presented at Dagstuhl Feb
                 2004. Generic to evolutionary computation, rather than
                 specifically on GP.}, coden = {TCSCDI},
	keywords = {Algorithms, Artificial Complexity, Computational Computing, Data Evolutionary Intelligence, Learning, Multiagent Neural Structures Systems algorithms, and genetic programming, }
}

@inproceedings{alt96*67,
	title = {Genetic fitness optimization using rapidly mixing
                 {Markov} chains},
	address = {Berlin},
	author = {Paul Vitanyi},
	booktitle = {Proceedings of the 7th International Workshop on
                 Algorithmic Learning Theory},
	editor = {Setsuo Arikawa and Arun K. Sharma},
	month = {October~23--25},
	pages = {67--82},
	publisher = {Springer-Verlag},
	series = {LNAI},
	volume = {1160},
	year = {1996},
	biburl = {http://www.bibsonomy.org/bibtex/2a15973321d28205cf9da48b038cdb41a/brazovayeye},
	isbn = {3-540-61863-5}, notes = {see also \cite{vitanyi:1997:gfourmmc} and
                 \cite{Vitanyi:2000:DEP}},
	keywords = {imported }
}

@techreport{vitanyi:1997:gfourmmc,
	title = {Genetic Fitness Optimization Using Rapidly Mixing
                 Markov Chains},
	address = {Computer Science, Royal Holloway, Egham, Surrey,
                 England},
	author = {Paul Vitanyi},
	institution = {NeuroCOLT},
	month = {February},
	number = {NC-TR-005},
	type = {technical report},
	url = {http://www.neurocolt.com/abs/1997/abs97005.html},
	year = {1997},
	biburl = {http://www.bibsonomy.org/bibtex/22eaf8620b682c12d878e74029d6bcefd/brazovayeye},
	abstract = {A notion of highly probable fitness optimization
                 through evolutionary computing runs on small size
                 populations in a very general setting is proposed. This
                 has applications to evolutionary learning. Based on
                 rapidly mixing Markov chains, the approach pertains to
                 most types of evolutionary genetic algorithms, genetic
                 programming and the like. For systems having associated
                 rapidly mixing Markov chains and appropriate stationary
                 distributions the new method finds optimal programs
                 (individuals) with probability almost 1.
                 Algorithmically, the novel approach prescribes a
                 strategy of executing many short computation runs,
                 rather than one long computation run. Given an
                 arbitrary evolutionary program it may be infeasible to
                 determine whether its associated matrix is rapidly
                 mixing. In our proposed structured evolutionary program
                 discipline, the development of the program and the
                 guaranty of the rapidly mixing property go hand in
                 hand. We conclude with a tentative toy example.},
	size = {17 pages}, email = {neurocolt@dcs.rhbnc.ac.uk}, notes = {See also \cite{alt96*67} and \cite{Vitanyi:2000:DEP}
                 Although refers several time to GP, approach is
                 evolutionary as a whole, ie not just GP},
	keywords = {computation evolutionary }
}