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Deterministic Treasure Hunt in the Plane with Angular Hints

Authors Sébastien Bouchard, Yoann Dieudonné, Andrzej Pelc, Franck Petit



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Author Details

Sébastien Bouchard
  • Sorbonne Université, CNRS, INRIA, LIP6, F-75005 Paris, France
Yoann Dieudonné
  • Laboratoire MIS, Université de Picardie Jules Verne, Amiens, France
Andrzej Pelc
  • Département d'informatique, Université du Québec en Outaouais, Gatineau, Canada
Franck Petit
  • Sorbonne Université, CNRS, INRIA, LIP6, F-75005 Paris, France

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Sébastien Bouchard, Yoann Dieudonné, Andrzej Pelc, and Franck Petit. Deterministic Treasure Hunt in the Plane with Angular Hints. In 29th International Symposium on Algorithms and Computation (ISAAC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 123, pp. 48:1-48:13, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.ISAAC.2018.48

Abstract

A mobile agent equipped with a compass and a measure of length has to find an inert treasure in the Euclidean plane. Both the agent and the treasure are modeled as points. In the beginning, the agent is at a distance at most D>0 from the treasure, but knows neither the distance nor any bound on it. Finding the treasure means getting at distance at most 1 from it. The agent makes a series of moves. Each of them consists in moving straight in a chosen direction at a chosen distance. In the beginning and after each move the agent gets a hint consisting of a positive angle smaller than 2 pi whose vertex is at the current position of the agent and within which the treasure is contained. We investigate the problem of how these hints permit the agent to lower the cost of finding the treasure, using a deterministic algorithm, where the cost is the worst-case total length of the agent's trajectory. It is well known that without any hint the optimal (worst case) cost is Theta(D^2). We show that if all angles given as hints are at most pi, then the cost can be lowered to O(D), which is optimal. If all angles are at most beta, where beta<2 pi is a constant unknown to the agent, then the cost is at most O(D^{2-epsilon}), for some epsilon>0. For both these positive results we present deterministic algorithms achieving the above costs. Finally, if angles given as hints can be arbitrary, smaller than 2 pi, then we show that cost Theta(D^2) cannot be beaten.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Computing methodologies → Mobile agents
Keywords
  • treasure hunt
  • deterministic algorithm
  • mobile agent
  • hint
  • plane

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