• Title/Summary/Keyword: ROBOSIM simulator

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Hexagon-Based Q-Learning Algorithm and Applications

  • Yang, Hyun-Chang;Kim, Ho-Duck;Yoon, Han-Ul;Jang, In-Hun;Sim, Kwee-Bo
    • International Journal of Control, Automation, and Systems
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    • v.5 no.5
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    • pp.570-576
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    • 2007
  • This paper presents a hexagon-based Q-leaning algorithm to find a hidden targer object with multiple robots. An experimental environment was designed with five small mobile robots, obstacles, and a target object. Robots went in search of a target object while navigating in a hallway where obstacles were strategically placed. This experiment employed 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.