Online Algorithms Modeled After Mousehunt
January 08, 2015 Β· Declared Dead Β· π arXiv.org
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Authors
Jeffrey Ling, Kai Xiao, Dai Yang
arXiv ID
1501.01720
Category
cs.DS: Data Structures & Algorithms
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
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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