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Computability

About: Computability is a research topic. Over the lifetime, 2829 publications have been published within this topic receiving 85162 citations.


Papers
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Proceedings ArticleDOI
25 Aug 1998
TL;DR: In this paper, an evolutionary method for solving the satisfiability problem is presented based on a parallel cellular genetic algorithm which performs global search on a random initial population of individuals and local selective generation of new strings according to new defined genetic operators.
Abstract: The paper presents an evolutionary method for solving the satisfiability problem. It is based on a parallel cellular genetic algorithm which performs global search on a random initial population of individuals and local selective generation of new strings according to new defined genetic operators. The algorithm adopts a diffusion model of information among chromosomes by realizing a two dimensional cellular automaton. Global search is then specialized in local search by changing the assignment of a variable that leads to the greatest decrease in the total number of unsatisfied clauses. A parallel implementation of the algorithm has been realized on a CS-2 parallel machine.

16 citations

Journal ArticleDOI
TL;DR: In this article, the existence of a computable presentation for a quasidiscrete linear ordering (L, adj) was studied. But the conditions for the existence were not specified.
Abstract: Let L be a quasidiscrete linear ordering. We specify some conditions for the existence of a computable presentation for L or for the structure (L, adj), where adj(x, y) is a predicate distinguishing adjacent elements.

16 citations

Journal Article
TL;DR: A competition between systems for doing exact real number computations was held in September 2000 and the results obtained are presented and a short evaluation of the different approaches used.
Abstract: A competition between systems for doing exact real number computations was held in September 2000. We present the results obtained and give a short evaluation of the different approaches used.

16 citations

Book ChapterDOI
30 Jun 2012
TL;DR: This paper shows how to capture failure detectors in each model so that both models become computationally equivalent, and introduces the notion of a "strongly correct" process which appears particularly well-suited to the iterated model, and presents simulations that prove the computational equivalence.
Abstract: The base distributed asynchronous read/write computation model is made up of n asynchronous processes which communicate by reading and writing atomic registers only. The distributed asynchronous iterated model is a more constrained model in which the processes execute an infinite number of rounds and communicate at each round with a new object called immediate snapshot object. Moreover, in both models up to n−1 processes may crash in an unexpected way. When considering computability issues, two main results are associated with the previous models. The first states that they are computationally equivalent for decision tasks. The second states that they are no longer equivalent when both are enriched with the same failure detector. This paper shows how to capture failure detectors in each model so that both models become computationally equivalent. To that end it introduces the notion of a "strongly correct" process which appears particularly well-suited to the iterated model, and presents simulations that prove the computational equivalence when both models are enriched with the same failure detector. The paper extends also these simulations to the case where the wait-freedom requirement is replaced by the notion of t-resilience.

16 citations

Journal ArticleDOI
TL;DR: Computable error bounds for the distances between feasible sets, optimal objective values, and optimal solution sets are given in terms of an upper bound for the condition number of a constraint system, a Lipschitz constant of the objective function, and the size of perturbation.
Abstract: We study computability and applicability of error bounds for a given semidefinite pro-gramming problem under the assumption that the recession function associated with the constraint system satisfies the Slater condition. Specifically, we give computable error bounds for the distances between feasible sets, optimal objective values, and optimal solution sets in terms of an upper bound for the condition number of a constraint system, a Lipschitz constant of the objective function, and the size of perturbation. Moreover, we are able to obtain an exact penalty function for semidefinite programming along with a lower bound for penalty parameters. We also apply the results to a class of statistical problems.

16 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202344
2022119
202189
202098
2019111
201897