Abstract
In this paper, a step-by-step procedure for designing a fuzzy decision making system for RoboCup agents is introduced and implemented. By using this mechanism agents can determine, which direction to look at. The development process and debugging of this approach are much less time consuming and very simple to follow, in comparison to other analytical hand coded implementations with complex conditions and many parameters in the code. The results show that, the methodology can be employed in many decision-making problems like the soccer agent’s case and other potential fields, to decrease the development time and improve the efficiency of a decision making system. Up until now, fuzzy systems have been used rarely by any of the participating teams in the annual RoboCup competitions. This paper could serve as the first inception for the design of a RoboCup agent, which uses internal fuzzy systems for many of its decision-making tasks.
This research was sponsored in part by the Ministry of Petroleum.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altrock, C.V.: Fuzzy Logic & Neurofuzzy Applications Explained. Prentice Hall PTR (1995)
Chen, M., et al.: Users Manual RoboCup Soccer Server. July 26 (2002) Available at http://sserver.sourceforge.net/docs/manual.pdf
Driankov, D., Hellendoorn, H.: Chaining of Fuzzy IF-THEN Rules in Mamdani-Controllers. Proc. IEEE Int. Conf. on Fuzzy Systems (1995)
Duman, H., Hu, H.: Fuzzy Logic for Behaviour Coordination and Multi-agent Formation in RoboCup. Int. Conf. on Recent Advances in Soft Computing (2000)
Jang, J.S.R.: ANFIS: Adaptive-Network-Based Fuzzy Inference Systems. IEEE Trans. on Systems, Man and Cybernetics, Vol. 23, No. 3, June (1993) 665–685
Jennings, N.R., Wooldridge, M.J.: Applications of Intelligent Agents. In: Agent Technologies: Foundations, Applications and Markets (1998)
Junji, N., et al.: Hierarchical Fuzzy Intelligent Controller for Gymnastic Bar Actions. J. of Advanced Computational Intelligence (1999)
Kawarabayashi, T., et al.: Zeng99 in RoboCup99. In: RoboCup99 Team Description: Simulation League (1999) Available at http://www.ep.liu.se/ea/cis/1999/007
Kosko, B.: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice Hall (1992)
Luce, R.D., Raiffa, H.: Games and Decisions. John Wiley & Sons Inc., New York (1957)
Marschak, J., Radner, R.: Economic Theory of Teams. Yale University Press (1972)
N. N.: FuzzyTECH 4.0 online Edition Manual. INFORM GmbH Aachn/Inform Software Corp., Chicago (1995)
Noda, I., Matsubara, H., Hiraki, K., Frank, I.: Soccer Server: a Tool for Research on Multi-agent Systems. In: Applied Artificial Intelligence (1997)
Raiffa, H.: Decision Analysis: Introductory Lectures on Choices Under Uncertainty. Reading, MA: Addison-Wesley (1968)
Reis, L.P., Lau, N.: FC Portugal Team Description: RoboCup 2000 Simulation League Champion. RoboCup 2000: Robot Soccer World Cup IV. Springer Verlag, Berlin (2001)
Riedmiller, M., et al.: Karlsruhe Brainstormers—a Reinforcement Learning Approach to Robotic Soccer. In: Stone, P., Balch, T., Kraetszchmar, G. (eds.): RoboCup 2000: Robot Soccer World Cup IV. Springer Verlag, Berlin (2001)
Tong, R.M., Bonissone, P.P.: Linguistic Solutions to Fuzzy Decision Problem. In: Zimmermann, H.J., Zadeh, L.A., Gines (eds.): Fuzzy Sets and Decision Analysis (1984)
Uchibe, E., Asada, M., et al.: Vision Based Reinforcement Learning for RoboCup: Towards Real Robot Competition. Proc. IROS’ 96 Workshop on RoboCup (1996)
Wooldridge, M., Jennings, N.R.: Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, Vol. 10, No. 2 (1995) 115–152
Yao, J., et al.: Architecture of Tsinghuaeolus. RoboCup 2001: Robot Soccer World Cup V. Springer Verlag, Berlin (2002)
Zimmermann, H.J.: Fuzzy Sets, Decision Making, and Expert Systems. Kluwer Academic Publishers (1987)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shahri, H.H. (2003). Towards Autonomous Decision Making in Multi-agent Environments Using Fuzzy Logic. In: Mařík, V., Pěchouček, M., Müller, J. (eds) Multi-Agent Systems and Applications III. CEEMAS 2003. Lecture Notes in Computer Science(), vol 2691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45023-8_24
Download citation
DOI: https://doi.org/10.1007/3-540-45023-8_24
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40450-7
Online ISBN: 978-3-540-45023-8
eBook Packages: Springer Book Archive