Stochastic Algorithms: Foundations and Applications : International Symposium, SAGA 2001 Berlin, Germany, December 13-14, 2001 Proceedings / edited by Kathleen Steinhöfel.

Format:

Book

Contributor:

Steinhöfel, Kathleen, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science 0302-9743 ; 2264.

Lecture Notes in Computer Science, 0302-9743 ; 2264

Language:

English

Subjects (All):

Probabilities.

Algorithms.

Computers.

Computer science--Mathematics.

Computer science.

Combinatorial analysis.

Mathematical statistics.

Probability Theory and Stochastic Processes.

Algorithm Analysis and Problem Complexity.

Computation by Abstract Devices.

Discrete Mathematics in Computer Science.

Combinatorics.

Probability and Statistics in Computer Science.

Local Subjects:

Probability Theory and Stochastic Processes.

Algorithm Analysis and Problem Complexity.

Computation by Abstract Devices.

Discrete Mathematics in Computer Science.

Combinatorics.

Probability and Statistics in Computer Science.

Physical Description:

1 online resource (CCXVI, 208 pages).

Edition:

First edition 2001.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001.

System Details:

text file PDF

Summary:

SAGA 2001, the ?rst Symposium on Stochastic Algorithms, Foundations and Applications, took place on December 13-14, 2001 in Berlin, Germany. The present volume comprises contributed papers and four invited talks that were included in the ?nal program of the symposium. Stochastic algorithms constitute a general approach to ?nding approximate solutions to a wide variety of problems. Although there is no formal proof that stochastic algorithms perform better than deterministic ones, there is evidence by empirical observations that stochastic algorithms produce for a broad range of applications near-optimal solutions in a reasonable run-time. The symposium aims to provide a forum for presentation of original research in the design and analysis, experimental evaluation, and real-world application of stochastic algorithms. It focuses, in particular, on new algorithmic ideas invo- ing stochastic decisions and exploiting probabilistic properties of the underlying problem domain. The program of the symposium re?ects the e?ort to promote cooperation among practitioners and theoreticians and among algorithmic and complexity researchers of the ?eld. In this context, we would like to express our special gratitude to DaimlerChrysler AG for supporting SAGA 2001. The contributed papers included in the proceedings present results in the following areas: Network and distributed algorithms; local search methods for combinatorial optimization with application to constraint satisfaction problems, manufacturing systems, motor control unit calibration, and packing ?exible - jects; and computational learning theory.

Contents:

Randomized Communication Protocols

Optimal Mutation Rate Using Bayesian Priors for Estimation of Distribution Algorithms

An Experimental Assessment of a Stochastic, Anytime, Decentralized, Soft Colourer for Sparse Graphs

Randomized Branching Programs

Yet Another Local Search Method for Constraint Solving

An Evolutionary Algorithm for the Sequence Coordination in Furniture Production

Evolutionary Search for Smooth Maps in Motor Control Unit Calibration

Some Notes on Random Satisfiability

Prospects for Simulated Annealing Algorithms in Automatic Differentiation

Optimization and Simulation: Sequential Packing of Flexible Objects Using Evolutionary Algorithms

Stochastic Finite Learning

Sequential Sampling Algorithms: Unified Analysis and Lower Bounds

Approximate Location of Relevant Variables under the Crossover Distribution.

Other Format:

Printed edition:

ISBN:

978-3-540-45322-2

9783540453222

Access Restriction:

Restricted for use by site license.