Learning soccer drills for the small size league of RoboCup
| dc.contributor.author | Quintero, Carlos | spa |
| dc.contributor.author | Rodríguez, Saith | spa |
| dc.contributor.author | Pérez, Katherín | spa |
| dc.contributor.author | López, Jorge | spa |
| dc.contributor.author | Rojas, Eyberth | spa |
| dc.contributor.author | Calderón, Juan | spa |
| dc.coverage.campus | CRAI-USTA Bogotá | spa |
| dc.date.accessioned | 2020-01-16T21:14:38Z | spa |
| dc.date.available | 2020-01-16T21:14:38Z | spa |
| dc.date.issued | 2015-01 | spa |
| dc.description.abstract | This paper shows the results of applying machine learning techniques to the problem of predicting soccer plays in the Small Size League of RoboCup. We have modeled the task as a multi-class classification problem by learning the plays of the STOx’s team. For this, we have created a database of observations for this team’s plays and obtained key features that describe the game state during a match. We have shown experimentally, that these features allow two learning classifiers to obtain high prediction accuracies and that most miss-classified observations are found early on the plays. | spa |
| dc.description.domain | http://unidadinvestigacion.usta.edu.co | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.doi | https://doi.org/10.1007/978-3-319-18615-3 32 | spa |
| dc.identifier.uri | http://hdl.handle.net/11634/20593 | |
| dc.relation.references | Salustowicz, R.P., Wiering, M.A., Schmidhuber, J.: Learning team strategies: soccer case studies. Mach. Learn. 33, 263–282 (1998) | spa |
| dc.relation.references | Stone, P.: Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer. MIT Press, United States (2000) | spa |
| dc.relation.references | Bianchi, R. A., Ribeiro, C. H., Costa, A. H.: Heuristic selection of actions in multiagent reinforcement learning. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 690–696. Morgan Kaufmann Publishers Inc., San Francisco (2007) | spa |
| dc.relation.references | Stone, Peter, Kuhlmann, Gregory, Taylor, Matthew E., Liu, Yaxin: Keepaway soccer: from machine learning testbed to benchmark. In: Bredenfeld, Ansgar, Jacoff, Adam, Noda, Itsuki, Takahashi, Yasutake (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 93–105. Springer, Heidelberg (2006) | spa |
| dc.relation.references | Duan, Y., Liu, Q., Xu, X.: Application of reinforcement learning in robot soccer. Eng. Appl. Artif. Intell. 20, 936–950 (2007) | spa |
| dc.relation.references | Karol, A., Nebel, B., Stanton, C., Williams, M.-A.: Case based game play in the RoboCup four-legged league. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020, pp. 739–747. Springer, Heidelberg (2004) | spa |
| dc.relation.references | Marling, C., Tomko, M., Gillen, M., Alexander, D., Chelberg, D.: Case-based reasoning for planning and world modeling in the RoboCup small size league. In: IJCAI Workshop on Issues in Designing Physical Agents for Dynamic Real-time Environments, Acapulco (2003) | spa |
| dc.relation.references | Wendler, J., Bach, J.: Recognizing and predicting agent behavior with case based reasoning. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020, pp. 729–738. Springer, Heidelberg (2004) | spa |
| dc.relation.references | Ros, R., L´opez de M`antaras, R., Arcos, J.-L., Veloso, M.M.: Team playing behavior in robot soccer: a case-based reasoning approach. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 46–60. Springer, Heidelberg (2007) | spa |
| dc.relation.references | Steffens, T.: Adapting similarity-measures to agent types in opponent modelling. In: Workshop on Modeling Other Agents from Observations at AAMA, pp. 125– 128, New York (2004) | spa |
| dc.relation.references | Ahmadi, M., Lamjiri, A.K., Nevisi, M.M., Habibi, J., Badie, K.: Using two-layered case-based reasoning for prediction in soccer coach. In: International Conference of Machine Learning. Models, Technologies and Applications, pp. 181–185. CSREA Press, Las Vegas (2003) | spa |
| dc.relation.references | Lattner, A.D., Miene, A., Visser, U., Herzog, O.: Sequential pattern mining for situation and behavior prediction in simulated robotic soccer. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 118–129. Springer, Heidelberg (2006) | spa |
| dc.relation.references | Riley, P., Veloso, M.: On behavior classification in adversarial environments. In: Parker, L.E., Bekey, G., Barhen, J. (eds.) Distributed Autonomous Robotic Systems, pp. 371–380. Springer, Tokyo (2000) | spa |
| dc.relation.references | Visser, U., Drcker, C., Hbner, S., Schmidt, E., Weland, H.: Sequential pattern mining for situation and behavior prediction in simulated robotic soccer. In: Stone, P., Balch, T., Kraetzschmar, G.K. (eds.) RoboCup 2000. LNCS (LNAI), vol. 2019, pp. 391–396. Springer, Heidelberg (2001) | spa |
| dc.relation.references | Faria, B.M., Reis, L.P., Lau, N., Castillo, G.: Machine learning algorithms applied to the classification of robotic soccer formations and opponent teams. In: 2010 IEEE Conference on Cybernetics and Intelligent Systems, pp. 344–349. IEEE Press, Singapore (2010) | spa |
| dc.relation.references | Trevizan, F., Veloso, M.: Learning opponent’s strategies in the RoboCup small size league. In: Proceedings of the AAMAS 2010 Workshop on Agents in Real-time and Dynamic Environments, pp. 45–52, Toronto (2010) | spa |
| dc.relation.references | Konur, S., Ferrein, A., Lakemeyer, G.: Learning decision trees for action selection in soccer agents. In: Proceedings of the ECAI-04 Workshop on Agents in Dynamic and Real-time Environments. IOS Press, Valencia (2004) | spa |
| dc.relation.references | Ledezma, A., Aler, R., Sanch´ıs, A., Borrajo, D.: Predicting opponent actions by observation. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds.) RoboCup 2004. LNCS (LNAI), vol. 3276, pp. 286–296. Springer, Heidelberg (2005) | spa |
| dc.relation.references | Chang, C.-C., Lin, C.-J.: LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Tech. 2, 1–27 (2011). http://www.csie.ntu.edu.tw/∼ cjlin/libsvm | spa |
| dc.relation.references | STOx’s team webpage. http://www.stoxs.org/index.php/en/projects/robocupssl-2 | spa |
| dc.rights | Atribución-NoComercial-CompartirIgual 2.5 Colombia | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/2.5/co/ | * |
| dc.subject.keyword | Machine learning | spa |
| dc.subject.keyword | RoboCup SSL | spa |
| dc.subject.keyword | Learning soccer drills | spa |
| dc.subject.keyword | Neural networks | spa |
| dc.subject.keyword | Support vector machines | spa |
| dc.title | Learning soccer drills for the small size league of RoboCup | spa |
| dc.type.category | Generación de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos | spa |
Archivos
Bloque original
1 - 1 de 1
Cargando...
- Nombre:
- Learning soccer drills for the small size league of RoboCup.pdf
- Tamaño:
- 786.84 KB
- Formato:
- Adobe Portable Document Format
- Descripción:
- Artículo SCOPUS
Bloque de licencias
1 - 1 de 1
- Nombre:
- license.txt
- Tamaño:
- 807 B
- Formato:
- Item-specific license agreed upon to submission
- Descripción: