Abstract
This paper presents a benchmark for multiagent systems specific to the simulator Soccerserver 2D, an environment to develop teams of robotic soccer, providing metrics and evaluation procedures for multiagent organization schemes, more specifically, coalitions formation. This benchmark has considered a MAS with two main levels, at least: (i) individual level, where agents are implemented from requisites of a social structure and considering its individual capabilities (roles, skills, etc); (ii) a social level, where all the social aspects of the MAS are specified (organization, plans, goals, etc.) and where the individual level of each agent instantiates these social knowledge to act in the system. The method proposed here has applied at social level, once it measures the quantity and quality of coalitions that arise in the environment.
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
Notes
- 1.
Here, we consider a complex environment those in the [20] sense: partially observable, stochastic, dynamic and unknown.
- 2.
Once team tokA1 was not available, it was not considered in experiments.
References
Almeida, F., Abreu, P.H., Lau, N., Reis, L.P.: An automatic approach to extract goal plans from soccer simulated matches. Soft. Comput. 17(5), 835–848 (2013)
Barrett, S., Stone, P., Kraus, S.: Empirical evaluation of ad hoc teamwork in the pursuit domain. In: Proceedings of 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011
Bezek, A.: Modeling multiagent games using action graphs. In: Proceedings of Modeling Other Agents from Observations (MOO 2004) (2004)
Chen, M., Foroughi, E., Heintz, F., Huang, Z.X., Kapetanakis, S., Kostiadis, K., Johan Kummeneje, I.N., Obst, O., Riley, P., Timo Steffens, Y.W., Yin, X.: RoboCup Soccer Server: for Soccer Server Version 7.07 and later, May 2001. www.robocup.org
Cliff, O.M., Lizier, J.T., Wang, X.R., Wang, P., Obst, O., Prokopenko, M.: Towards quantifying interaction networks in a football match. In: Behnke, S., Veloso, M., Visser, A., Xiong, R. (eds.) RoboCup 2013. LNCS (LNAI), vol. 8371, pp. 1–12. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44468-9_1
da Cunha Abreu, P.M.H.: Artificial intelligence methodologies applied to the analysis and optmization of soccer teams performance. Master’s thesis, Faculdade de Engenharia da Universidade do Porto - Universidade do Porto (2011)
da Rosa, A.M., Gularte, A., Jung, M., Gonçalves, E.M.: Two different perspectives about how to specify and implement multiagent systems. In: Anais do VII Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações, pp. 141–144 (2013)
Drogoul, A., Collinot, A.: Applying an agent-oriented methodology to the design of artificial organizations: a case study in robotic soccer. Auton. Agents Multi-agent Syst. 1(1), 113–129 (1998)
Fox, M.S.: An organizational view of distributed systems. IEEE Trans. Syst. Man Cybern. 11(1), 70–80 (1981)
Horling, B., Lesser, V.: A survey of multi-agent organizational paradigms. Knowl. Eng. Rev. 19(04), 281–316 (2004)
Houhamdi, Z.: Multi-agent system testing: a survey. Int. J. Adv. Comput. 2(6), 135–141 (2011)
Hsu, F.-H.: IBM’s deep blue chess grandmaster chips. IEEE Micro 19(2), 70–81 (1999)
Iglesias, J.A., Ledezma, A., Sanchis, A.: The RoboCup agent behavior modeling challenge (2010)
Karimi, M., Ahmazadeh, M.: Mining RoboCup log files to predict own and opponent action. Int. J. Adv. Res. Comput. Sci. 5(6), 27–32 (2014)
Kitano, H., Asada, M., Kuniyoshi, Y., Noda, I., Osawa, E.: RoboCup: the robot world cup initiative. In: The First International Conference on Autonomous Agent (Agents 1997) (1997)
Miles, S., Winikoff, M., Cranefield, S., Nguyen, C.D., Perini, A., Tonella, P., Harman, M., Luck, M.: Why testing autonomous agents is hard and what can be done about it. In: AOSE Technical Forum (2010). http://www.pa.icar.cnr.it/cossentino/AOSETF10/docs/miles.pdf
Nardi, D., Noda, I., Ribeiro, F., Stone, P., von Stryk, O., Veloso, M.: RoboCup soccer leagues. AI Mag. 35(3), 77–85 (2014)
Nguyen, C.D., Miles, S., Perini, A., Tonella, P., Harman, M., Luck, M.: Evolutionary testing of autonomous software agents. Auton. Agents Multi-agent Syst. 25(2), 260–283 (2012)
Riley, P., Stone, P., Veloso, M.: Layered disclosure: revealing agents’ internals. In: Castelfranchi, C., Lespérance, Y. (eds.) ATAL 2000. LNCS (LNAI), vol. 1986, pp. 61–72. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-44631-1_5
Russel, S., Norvig, P.: Artificial Intelligence, A Modern Approach. Alan Apt (1995)
Sivakumar, N., Vivekanandan, K.: Agent oriented software testing-role oriented approach. Editorial Preface 3(12) (2012)
Stone, P., Kaminka, G.A., Kraus, S., Rosenschein, J.S., et al.: Ad hoc autonomous agent teams: collaboration without pre-coordination. In: AAAI (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Gonçalves, E.M.N., Adamatti, D., dos Santos Klipp, T. (2018). Benchmark for Coalitions at Multiagent Systems in a Robotic Soccer Simulation Environment. In: Dimuro, G., Antunes, L. (eds) Multi-Agent Based Simulation XVIII. MABS 2017. Lecture Notes in Computer Science(), vol 10798. Springer, Cham. https://doi.org/10.1007/978-3-319-91587-6_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-91587-6_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91586-9
Online ISBN: 978-3-319-91587-6
eBook Packages: Computer ScienceComputer Science (R0)