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	Algorithm - Encyclopedia.WorldSearch (Site not responding. Last check: 2007-11-07)
		Algorithms can be implemented by computer programs, although often in restricted forms; an error in the design of an algorithm for solving a problem can lead to failures in the implementing program.
		Algorithms are not only implemented as computer programs, but often also by other means, such as in a biological neural network (for example, the human brain implementing arithmetic or an insect relocating food), or in electric circuits or in a mechanical device.
		The first case of an algorithm written for a computer was Ada Byron's notes on the analytical engine written in 1842, for which she is considered by many to be the world's first programmer.
	encyclopedia.worldsearch.com /algorithm.htm (2202 words)

	Randomized algorithm - Wikipedia, the free encyclopedia
		A randomized algorithm is an algorithm which is allowed to flip a truly random coin.
		The former type are called Las Vegas algorithms, and the latter are Monte Carlo algorithms (related to the Monte Carlo method for simulation).
		Historically, the study of randomized algorithms was spurred by the discovery by Miller and Rabin in 1976 that the problem of determining the primality of a number can be solved efficiently by a randomized algorithm.
	en.wikipedia.org /wiki/Probabilistic_algorithm (1245 words)

	probabilistic algorithm (Site not responding. Last check: 2007-11-07)
		In mathematics, a probabilistic algorithm is an algorithm that with very high probability gives a correct answer, but not with certainty.
		Such an algorithm may run much faster than one that is sure to give the right answer in every case, but it may also take longer than such an algorithm.
		One such algorithm, the Miller-Rabin primality test, relies on a binary relation between two positive integers k and n that can be expressed by saying that k "is a witness to the compositeness of" n.
	www.yourencyclopedia.net /Probabilistic_algorithm.html (399 words)

	Encyclopedia article on Algorithm [EncycloZine] (Site not responding. Last check: 2007-11-07)
		Algorithms are essential to the way computers process information, because a computer program is essentially an algorithm that tells the computer what specific steps to perform (in what specific order) in order to carry out a specified task, such as calculating employees’ paychecks or printing students’ report cards.
		Probabilistic algorithms are those that make some choices randomly (or pseudo-randomly); for some problems, it can in fact be proved that the fastest solutions must involve some randomness.
		An example of this would be simulated annealing algorithms, a class of heuristic probabilistic algorithms that vary the solution of a problem by a random amount.
	encyclozine.com /Algorithm (2142 words)

	An algorithm for probabilistic planning (Site not responding. Last check: 2007-11-07)
		Abstract: We define the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of propositions representing the goal, a probability threshold, and actions whose effects depend on the execution-time state of the world and on random chance.
		Adopting a probabilistic model complicates the definition of plan success: instead of demanding a plan that provably achieves the goal, we seek plans whose probability of success exceeds the threshold.
		We prove that the algorithm is both sound and complete.
	www.cse.msu.edu /rlr/pub/Kushmerick1.html (151 words)

	Probabilistic algorithm (Site not responding. Last check: 2007-11-07)
		probabilistic algorithm genetic algorithm algorithm triangle tristrip layout genetic algorithm
		A Post-Darwinian Probabilistic Model A probabilistic model of biological evolution with a new interpretation of Darwinian natural selection and 3 examples: 1) 5 mass extinctions 2) hominization 3) the PO2PAL increase.
		Probabilistic Model Toolkit [free] Functions for inference and learning in various static and dynamic probabilistic models such as hidden Markov models, linear dynamic systems, Gaussian mixture models, and factor analyzers.
	www.serebella.com /encyclopedia/article-Probabilistic_algorithm.html (368 words)

	Randomized algorithm -- Facts, Info, and Encyclopedia article (Site not responding. Last check: 2007-11-07)
		A randomized algorithm is an (A precise rule (or set of rules) specifying how to solve some problem) algorithm which is allowed to flip a truly random coin.
		Formally, the algorithm's performance will be a (A variable quantity that is random) random variable determined by the random bits, with (hopefully) good (The sum of the values of a random variable divided by the number of values) expected value.
		Historically, the study of randomized algorithms was spurred by the discovery by (Click link for more info and facts about Miller and Rabin) Miller and Rabin in 1976 that the problem of determining the (The property of being a prime number) primality of a number can be solved efficiently by a randomized algorithm.
	www.absoluteastronomy.com /encyclopedia/r/ra/randomized_algorithm.htm (1295 words)

	18
		Probabilistic algorithms is one of the most active and rapidly growing areas of research in computer science.
		The expected behavior of a randomized algorithm is no better than the average behavior of its associated deterministic algorithm and is usually a little worse due to such things as the overhead of calls to a random number generator.
		algorithm is a probabilistic algorithm that has a certain probability of returning the correct answer whatever input is considered.
	www.ececs.uc.edu /~jpaul/472/prob.html (2907 words)

	Probabilistic algorithm (Site not responding. Last check: 2007-11-07)
		A separate article deals with the probabilistic method, which should not be confused with the topic of this article.
		In mathematics, a probabalistic algorithm is an algorithm that with very high probability gives a correct answer, but not with certainty.
		One such algorithm, created by Michael Rabin[?], relies on a binary relation between two positive integers k and n that can be expressed by saying that k "is a witness to the compositeness of" n.
	www.eurofreehost.com /pr/Probabilistic_algorithm.html (367 words)

	Probabilistic algorithm (Site not responding. Last check: 2007-11-07)
		A randomized algorithm is an algorithm which is allowed to flipa truly random coin.
		The most basic randomized complexity class is RP, which is the class of decision problems for which there is an efficient (polynomial time)randomized algorithm (or probabilistic Turing machine) which recognizes NO-instances with absolute certainty and recognizesYES-instances with a probability of at least 1/2.
		Problem classes having (possiblynonterminating) algorithms with polynomial time average case running time whose output is always correct are said to be in ZPP.
	www.therfcc.org /probabilistic-algorithm-36972.html (1092 words)

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		Probabilistic algorithms, such as Monte-Carlo trials, genetic algorithms, hill-climbing, and simulated annealing, are approximate methods for intractable problems, i.e., problems for which no efficient exact algorithms are believed to exist.
		A typical probabilistic algorithm tries to approximately solve a problem with a vast number of potential solutions by first generating a smaller set of candidate solutions.
		Then, the algorithm tries to improve the set of candidate solution by means of some probabilistic computations, such as simulated annealing, hill-climbing, cross-over, or Monte-Carlo trials.
	www.chapman.edu /~radenski/research/paradigm-sp/docs/samples.html (568 words)

	Nat' Academies Press, Probability and Algorithms (1992)
		The point is rather to see that the sampling techniques of political pollsters are actually probabilistic algorithms; one uses exogenous randomization to obtain an approximation to a problem that would be prohibitively expensive to answer exactly.
		An issue that emerges at this point is that for algorithms that do not return an exact solution, there are two compelling dimensions along which to measure performance: the quality of the solution obtained and the amount of time needed to obtain that solution.
		The second algorithm requires a little more knowledge to implement efficiently, but for people who have had some exposure to the subject of data structures there are some off-the-shelf tools that come to mind almost immediately.
	www.nap.edu /books/0309047765/html/1.html (6032 words)

	Please see PDF version
		The asymptotic behavior of the optimal solution of the DTSP is determined, and this result is used to establish an toptimal probabilistic algorithm for solving the DTSP in polynomial time.
		The main consequence of this asymptotic relationship is the existence of a probabilistically efficient algorithm for the DTSP.
		The results of this article are pointed toward the establishment of algorithms which perform well in terms of the expected length of the solution obtained.
	www-stat.wharton.upenn.edu /~steele/Papers/HTML/Paftdt.html (2162 words)

	Citations: Probabilistic Algorithms for Testing Primality - Rabin (ResearchIndex)
		It is quite similar to probabilistic robustness [1] which is based on the idea that if one can be satisfied with probabilistic performance guarantees, then one can often achieve robustness over a much larger range of situations.
		However, the problem is not yet known to be in P : while the algorithms of [Rab80, SS77] are randomized, the algorithm of [Mil76] is in P only under an unproved number theoretic hypothesis (there exists a small quadratic nonresidue) All these algorithms are based on various properties of....
		are randomized, the algorithm of [Mil76] is in P only under an unproved number theoretic hypothesis (there exists a small quadratic nonresidue) All these algorithms are based on various properties of prime numbers, e.g.
	citeseer.ist.psu.edu /context/29583/0 (1781 words)

	From The Cover: An algorithm for progressive multiple alignment of sequences with insertions -- Löytynoja and ...
		The alignment of D-loop sequences inferred with the probabilistic algorithm using the JC substitution model but disabling the correction for insertion events.
		The alignment of D-loop sequences inferred with the probabilistic algorithm using the JC substitution model and the correction to distinguish insertions from deletions.
		The alignment of D-loop sequences inferred with the probabilistic algorithm using the JC substitution model and the correction to distinguish insertions from deletions; the sites once inferred as insertion are forced to be skipped over in the subsequent alignments.
	www.pnas.org /cgi/content/full/0409137102/DC1 (536 words)

	Formal Verification of Probabilistic Algorithms (Site not responding. Last check: 2007-11-07)
		This allows the definition of the probability space we use to model a random bit generator, which informally is a stream of coin-flips, or technically an infinite sequence of IID Bernoulli(1/2) random variables.
		Probabilistic programs are modelled using the state-transformer monad familiar from functional programming, where the random bit generator is passed around in the computation.
		We also introduce a technique for reducing properties of a probabilistic while loop to properties of programs that are guaranteed to terminate: these can then be established using induction and standard methods of program correctness.
	www.cl.cam.ac.uk /~jeh1004/research/papers/thesis.html (275 words)

	Fast Statistical Timing Analysis By Probabilistic Event Propagation
		In this paper, we propose a new statistical timing analysis algorithm, which produces arrival-time random variables for all internal signals and primary outputs for cell-based designs with all cell delays modeled as random variables.
		The new algorithm is deterministic and flexible in controlling run time and accuracy.
		Experiments show that this approximate algorithm speeds up the statistical timing analysis by at least an order of magnitude and produces results with small errors when compared with Monte Carlo methods.
	www.gigascale.org /pubs/113.html (292 words)

	Probabilistic Algorithm Encyclopedia Article, Definition, History, Biography (Site not responding. Last check: 2007-11-07)
		Looking For probabilistic algorithm - Find probabilistic algorithm and more at Lycos Search.
		Find probabilistic algorithm - Your relevant result is a click away!
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	www.alienartifacts.com /search/encyclopedia/Probabilistic_algorithm (1390 words)

	BioMed Central \| Full text \| PhyME: A probabilistic algorithm for finding motifs in sets of orthologous sequences
		These algorithms [1-6] do not have the notion of sequence orthology built into them, and are therefore typically run on sequences from the same species.
		The algorithm PhyloCon (Wang and Stormo [20]) extends the greedy algorithm of CONSENSUS (Hertz et al.
		In the probabilistic process that is assumed to generate sequences, the transition probability does not depend on the previous choice(s) made during the process, meaning that the HMM is of zeroth order, nor on the position in the sequence, meaning that any information about spatial distribution of motifs is ignored.
	www.biomedcentral.com /1471-2105/5/170 (9498 words)

	exploreLV
		However, non-exhaustive probabilistic exploration has a major advantage over exhaustive exploration by backtrack, that is its higher valid structures finding rate.
		Even if this probabilistic approach to explore a molecules tertiary structures seems quite naive, it has the benefit of never become trapped in an excessively fastidious and useless exploration of a sterile sub-tree due to a shallower residue conformation.
		In fact, the chances are that a newly found tertiary structure by probabilistic exploration will be totally different from its predecessor, which aint the case in exploration by backtrack.
	www-lbit.iro.umontreal.ca /mcsym/doc/node41.html (372 words)

	[No title]
		For example, I once bumped into a cryptographer who had completely misunderstood various theorems because---having never seen the definition of the word ``random''---he incorrectly assumed that a ``random function from S to T'' was a function from S to T. You can add to these costs by introducing new non-restrictive adjectives.
		Or is an algorithm required to flip at least one coin to qualify as a probabilistic algorithm?
		Other people define ``probabilistic algorithm'' without this requirement, and then state theorems about ``probabilistic algorithms'' to cover algorithms that might flip coins and algorithms that don't.
	cr.yp.to /bib/devil-name.html (703 words)

	A Probabilistic Algorithm for Molecular Clustering
		The aim of this work is to present a probabilistic algorithm for this task.
		When K is small the search is faster but finds less pairs, so that the number of times it has to be repeated to obtain the same number of pairs can be larger than for higher values of K.
		The optimal value of K also depends on the efficiency of the different stages of the algorithm.
	algo.inria.fr /seminars/sem97-98/cazals.html (650 words)

	KSL-89-31 (Site not responding. Last check: 2007-11-07)
		Chavez, M. Cooper, G. An Empirical Evaluation of a Randomized Algorithm for Probabilistic Inference.
		An empirical evaluation of a randomized algorithm for probabilistic inference KNET is an environment for constructing probabilistic, knowledge-based systems within the axiomatic framework of decision theory.
		In this article, we summarize a randomized algorithm for probabilistic inference and analyze its performance mathematically.
	www-ksl.stanford.edu /KSL_Abstracts/KSL-89-31.html (251 words)

	PROBABILISTIC SEARCH
		However, it seems that nobody implemented it for experimental applications, perhaps in fear of the ominous ``constant factor'' which may be large.
		The experimental results obtained with the probabilistic algorithm (see section 4) are very similar to those obtained by the original universal search procedure.
		Towards this purpose, the probabilistic search algorithm randomly generates programs written in a general assembler-like programming language based on sequences of integers.
	www.idsia.ch /~juergen/icmlkolmogorov/node3.html (1333 words)

	Computer Science Colloquium (Site not responding. Last check: 2007-11-07)
		It is conjectured that every poly-time probabilistic algorithm can be derandomized into a poly-time deterministic algorithm.
		(A recent example is the deterministic poly-time algorithm for primality testing of Agarwal et al.) The hardness versus randomness paradigm attempts to derandomize all probabilistic algorithms by using unproven assumptions that resemble The P versus NP assumption.
		It follows that we can derandomize any efficient probabilistic algorithm by running it with "pseudo-random" bits instead of truly random bits.
	www.cs.technion.ac.il /~colloq/20030304_14_30_Shaltiel.html (162 words)

	Reliability Versus Cost: Design of a Probabilistic Broadcast Algorithm - Ciuffoletti (ResearchIndex) (Site not responding. Last check: 2007-11-07)
		Abstract: We propose a probabilistic algorithm to solve the problem of distributed broadcast.
		A simple diffusion algorithm is introduced, and its reliability is evaluated.
		The cost and reliability of the probabilistic algorithm are compared with the corresponding deterministic algorithm.
	citeseer.ist.psu.edu /ciuffoletti94reliability.html (444 words)

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