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On the List Update Problem with Advice

  • Joan Boyar
  • Shahin Kamali
  • Kim S. Larsen
  • Alejandro López-Ortiz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8370)

Abstract

We study the online list update problem under the advice model of computation. Under this model, an online algorithm receives partial information about the unknown parts of the input in the form of some bits of advice generated by a benevolent offline oracle. We show that advice of linear size is required and sufficient for a deterministic algorithm to achieve an optimal solution or even a competitive ratio better than 15/14. On the other hand, we show that surprisingly two bits of advice is sufficient to break the lower bound of 2 on the competitive ratio of deterministic online algorithms and achieve a deterministic algorithm with a competitive ratio of \(1.\bar{6}\). In this upper-bound argument, the bits of advice determine the algorithm with smaller cost among three classical online algorithms.

Keywords

Competitive Ratio Online Algorithm Advice Model Deterministic Algorithm Aggregate Cost 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Joan Boyar
    • 1
  • Shahin Kamali
    • 2
  • Kim S. Larsen
    • 1
  • Alejandro López-Ortiz
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of Southern DenmarkOdense MDenmark
  2. 2.School of Computer ScienceUniversity of WaterlooWaterlooCanada

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