1,720,986 research outputs found
Optimal approximation schedules for a class of iterative algorithms, with an application to multigrid value iteration
No full textMany iterative algorithms employ operators which are difficult to evaluate exactly, but for which a graduated range of approximations exist. In such cases, coarse-to-fine algorithms are often used, in which a crude initial operator approximation is gradually refined with new iterations. In such algorithms, because the computational complexity increases over iterations, the algorithm's convergence rate is properly calculated with respect to cumulative computation time. This suggests the problem of determining an optimal rate of refinement for the operator approximation. This paper shows that, for linearly convergent algorithm, the optimal rate of refinement approaches the rate of convergence of the exact algorithm itself, regardless of the tolerance-complexity relationship. We illustrate this result with an analysis of coarse-to-fine grid algorithms for Markov decision processes with continuous state spaces. Using the methods proposed here we deduce an algorithm that presents optimal complexity results and consists solely of a non-adaptive schedule for the gradual decrease of grid size.</p
Optimal approximation schedules for iterative algorithms with application to dynamic programming
No full textMany iterative algorithms rely on operators which may be difficult or impossible to evaluate exactly, but for which approximations are available. Furthermore, a graduated range of approximations may be available, inducing a functional relationship between computational complexity and approximation tolerance. In such a case, a reasonable strategy would be to vary tolerance over iterations, starting with a cruder approximation, then gradually decreasing tolerance as the solution is approached. In this article, it is shown that under general conditions, for linearly convergent algorithms the optimal choice of approximation tolerance convergence rate is the same linear convergence rate as the exact algorithm itself, regardless of the tolerance/complexity relationship. We illustrate this result by presenting a partial information value iteration (PIVI) algorithm for discrete time dynamic programming problems. The proposed algorithm makes use of increasingly accurate partial model information in order to decrease the computational burden of the standard value iteration algorithm. The algorithm is applied to a stochastic network example and compared to value iteration for the purpose of benchmarking.</p
Toward an optimized value iteration algorithm for average cost Markov decision processes
No full textIn this paper we propose a technique to accelerate the convergence rate of the value iteration (VI) algorithm applied to discrete average cost Markov decision processes (MDP). The convergence rate is measured with respect to the total computational effort instead of the iteration counter. Such a rate definition makes it possible to compare different classes of algorithms, which employ distinct and possibly variable updating schemes. A partial information value iteration (PIVI) algorithm is proposed that updates an increasingly accurate approximate version of the original problem with a view toward saving computations at the early stages of the algorithm, when one is typically far from the optimal solution. The PIVI overall computational effort is compared with that of the classical VI algorithm for a broad set of parameters. The results suggest that a suitable choice of parameters can lead to significant computational savings in the process of finding the optimal solution for discrete MDP under the average cost criterion.</p
Stability and optimality of a discrete production and storage model with uncertain demand
No full textIn this work, we present a discrete model to the production and storage problem with multiple production stages and a single Anal product, subject to random demand. We present some conditions under which the optimal policy generates positive recurrent states. In addition, we derive a dinamic programming procedure to seek the optimal solution to the problem and provide some numerical examples.</p
Accelerating the convergence of value iteration by using partial transition functions
No full textThis work proposes an algorithm that makes use of partial information to improve the convergence properties of the value iteration algorithm in terms of the overall computational complexity. The algorithm iterates on a series of increasingly refined approximate models that converges to the true model according to an optimal linear rate, which coincides with the convergence rate of the original value iteration algorithm. The paper investigates the properties of the proposed algorithm and features a series of switchover queue examples which illustrates the efficacy of the method.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
