An Introduction to Online Computation - Komm, Dennis
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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.

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Produktbeschreibung
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.
Autorenporträt
Dr. Dennis Komm is a lecturer in the Chair of Information Technology and Education at ETH Zürich. His research interests include approximation algorithms for hard optimization problems, re-optimization of optimization problems, and advice complexity in different setups and environments.
Rezensionen
"This book is about online algorithms for optimization problems. ... The book can be used as a textbook on the undergraduate level. ... The book can also be used for self-study and as a reference. Its strength in this regard is enhanced by the historical notes at the end of each chapter and a comprehensive bibliography." (Bogdan S. Chlebus,Mathematical Reviews, March, 2018)

"This text is an important contribution to the field of online algorithms. ... Without a doubt, this text is a must-read for anyone seriously pursuing the analysis of algorithms, particularly online versions of those algorithms." (Michael Goldberg and R. Goldberg, Computing Reviews, October, 2017)