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To Explore or to Exploit? Learning Humans’ Behaviour to Maximize Interactions with Them

  • Miroslav KulichEmail author
  • Tomáš Krajník
  • Libor Přeučil
  • Tom Duckett
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9991)

Abstract

Assume a robot operating in a public space (e.g., a library, a museum) and serving visitors as a companion, a guide or an information stand. To do that, the robot has to interact with humans, which presumes that it actively searches for humans in order to interact with them. This paper addresses the problem how to plan robot’s actions in order to maximize the number of such interactions in the case human behavior is not known in advance. We formulate this problem as the exploration/exploitation problem and design several strategies for the robot. The main contribution of the paper than lies in evaluation and comparison of the designed strategies on two datasets. The evaluation shows interesting properties of the strategies, which are discussed.

Keywords

Distant experimentation e-Learning Mobile robots Robot programming 

Notes

Acknowledgments

This work has been supported by the Technology Agency of the Czech Republic under the project no. TE01020197 “Centre for Applied Cybernetics” and by the EU ICT project 600623 ‘STRANDS’.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Miroslav Kulich
    • 1
    Email author
  • Tomáš Krajník
    • 2
  • Libor Přeučil
    • 1
  • Tom Duckett
    • 2
  1. 1.Czech Institute of Informatics, Robotics, and CyberneticsCzech Technical University in PraguePragueCzech Republic
  2. 2.Lincoln Centre for Autonomous SystemsUniversity of LincolnLincolnUK

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