Abstract
This paper presents the hexagon-based Q-leaning for object search with multiple robots. We set up an experimental environment with five 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 three control algorithms: a random search, 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.
This research was supported by the project of Developing SIC and Applications under the Next Generation Technologies program in 2000: The Ministry of Commerce, Industry, and Energy in Korea.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Parker, L.: Adaptive Action Selection for Cooperative Agent Teams. In: Proc. of 2nd Int. Conf. on Simulation of Adaptive Behavior, pp. 442–450 (1992)
Ogasawara, G., Omata, T., Sato, T.: Multiple Movers Using Distributed, Decision-Theoretic Control. In: Proc. of Japan-USA Symp. on Flexible Automation, vol. 1, pp. 623–630 (1992)
Ballard, D.: An Introduction to Natural Computation. The MIT Press, Cambridge (1997)
Jang, J., Sun, C., Mizutani, E.: Neuro-Fuzzy and Soft Computing. Prentice-Hall, New Jersey (1997)
Ashley, W., Balch, T.: Value-Based Observation with Robot Teams (VBORT) using Probabilistic Techniques. In: Proc. of Int. Conf. on Advanced Robotics (2003)
Ashley, W., Balch, T.: Value-Based Observation with Robot Teams (VBORT) for Dynamic Targets. In: Proc. of Int. Conf. on Intelligent Robots and Systems (2003)
Park, J.B., Lee, B.H., Kim, M.S.: Remote Control of a Mobile Robot Using Distance-Based Reflective Force. In: Proc. of IEEE Int. Conf. on Robotics and Automation, vol. 3, pp. 3415–3420 (2003)
Patterson, D., Hennessy, J.: Computer Organization and Design, 3rd edn. Morgan-Kaufmann, Korea (2005)
Mitchell, T.: Machine Learning. McGraw-Hill, Singapore (1997)
Clausen, C., Wechsler, H.: Quad-Q-Learning. IEEE Trans. on Neural Network 11, 279–294 (2000)
Yoon, H.U., Whang, S.H., Kim, D.W., Sim, K.B.: Strategy of Cooperative Behaviors of Distributed Autonomous Robotic Systems. In: Proc. of 10th Int. Symp. on Artificial Life and Robotics, pp. 151–154 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yoon, HU., Sim, KB. (2005). Hexagon-Based Q-Learning for Object Search with Multiple Robots. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_88
Download citation
DOI: https://doi.org/10.1007/11539902_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28320-1
Online ISBN: 978-3-540-31863-7
eBook Packages: Computer ScienceComputer Science (R0)