An Introduction to Online Computation [recurso electrónico] : Determinism, Randomization, Advice / by Dennis Komm.

Por: Komm, Dennis [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: Texto

TextoSeries Texts in Theoretical Computer Science. An EATCS SeriesEditor: Cham : Springer International Publishing : Imprint: Springer, 2016Descripción: XV, 349 p. 58 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319427492Tema(s): Computer science | Computers | Algorithms | Computer Science | Theory of Computation | AlgorithmsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 004.0151 Clasificación LoC:QA75.5-76.95Recursos en línea: Libro electrónico Texto

Contenidos:

Introduction -- Randomization -- Advice Complexity -- The k-Server Problem -- Job Shop Scheduling -- The Knapsack Problem -- The Bit Guessing Problem -- Problems on Graphs.

En: Springer eBooksResumen: This textbook explains online computation in different settings, with particular emphasis on randomization and advice complexity. These settings are analyzed for various online problems such as the paging problem, the k-server problem, job shop scheduling, the knapsack problem, the bit guessing problem, and problems on graphs. This book is appropriate for undergraduate and graduate students of computer science, assuming a basic knowledge in algorithmics and discrete mathematics. Also researchers will find this a valuable reference for the recent field of advice complexity.

Existencias ( 1 )
Notas de título ( 2 )

Existencias
Tipo de ítem	Biblioteca actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras
Libro Electrónico	Biblioteca Electrónica	Colección de Libros Electrónicos		1	No para préstamo

Introduction -- Randomization -- Advice Complexity -- The k-Server Problem -- Job Shop Scheduling -- The Knapsack Problem -- The Bit Guessing Problem -- Problems on Graphs.

This textbook explains online computation in different settings, with particular emphasis on randomization and advice complexity. These settings are analyzed for various online problems such as the paging problem, the k-server problem, job shop scheduling, the knapsack problem, the bit guessing problem, and problems on graphs. This book is appropriate for undergraduate and graduate students of computer science, assuming a basic knowledge in algorithmics and discrete mathematics. Also researchers will find this a valuable reference for the recent field of advice complexity.