Online Algorithms Modeled After Mousehunt

نویسندگان

  • Jeffrey Ling
  • Kai Xiao
  • Dai Yang
چکیده

In this paper we study a variety of novel online algorithm problems inspired by the game Mousehunt. We consider a number of basic models that approximate the game, and we provide solutions to these models using Markov Decision Processes, deterministic online algorithms, and randomized online algorithms. We analyze these solutions’ performance by deriving results on their competitive ratios.

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عنوان ژورنال:
  • CoRR

دوره abs/1501.01720  شماره 

صفحات  -

تاریخ انتشار 2014