Hexagon-based q-learning to find a hidden target object

  • Authors:
  • Han-Ul Yoon;Kwee-Bo Sim

  • Affiliations:
  • School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea;School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea

  • Venue:
  • CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
  • Year:
  • 2005

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Abstract

This paper presents the hexagon-based Q-leaning to find a hidden target object with multiple robots. We set up an experimental environment with three small mobile robots, obstacles, and a target object. The robots were out to search for a target object while navigating in a hallway where some obstacles were placed. In this experiment, we used two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.