Case Based Game Play in the RoboCup Four-Legged League Part I The Theoretical Model

  • Alankar Karol
  • Bernhard Nebel
  • Christopher Stanton
  • Mary-Anne Williams
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3020)


Robot Soccer involves planning at many levels, and in this paper we develop high level planning strategies for robots playing in the RoboCup Four-Legged League using case based reasoning. We develop a framework for developing and choosing game plays. Game plays are widely used in many team sports e.g. soccer, hockey, polo, and rugby. One of the current challenges for robots playing in the RoboCup Four-Legged League is choosing the right behaviour in any game situation. We argue that a flexible theoretical model for using case based reasoning for game plays will prove useful in robot soccer. Our model supports game play selection in key game situations which should in turn significantly advantage the team.


  1. 1.
    Chalup, S., Creek, N., Freeston, L., Lovell, N., Marshall, J., Middleton, R., Murch, C., Quinlan, M., Shanks, G., Stanton, C., Williams, M.-A.: When NUbots Attack! The 2002 NUbots Team Report, Newcastle Robotics Laboratory Report (2002),
  2. 2.
    Cook, W., Rohe, A.: Computing minimum-weight perfect matchings. INFORMS Journal on Computing 11(2), 138–148 (1999)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Gabel, T., Veloso, M.: Selecting Heterogenous Team Players by Case-Based Reasoning: A Case Study in Robotic Soccer simulation. CMU-CS-01-165 (December 2001)Google Scholar
  4. 4.
    Gardenfors, P.: Conceptual Spaces: The Geometry of Thought. A Bradford Book. MIT Press, Cambridge (2000)Google Scholar
  5. 5.
    Gärdenfors, P., Williams, M.-A.: Reasoning about Categories in Conceptual Spaces. In: Proceedings of the Joint Conference of Artificial Intelligence, pp. 385–392. Morgan Kaufman, San Francisco (2001)Google Scholar
  6. 6.
    Gärdenfors, P., Williams, M.-A.: Building Rich and Grounded Robot World Models from Sensors and Knowledge Resources: A Conceptual Spaces Approach. In: The Proceedings of the International Symposium on Autonomous Mini-robots for Research and Edutainment, pp. 123 – 133 (2003)Google Scholar
  7. 7.
    Hahn, Ramscar: Similarity and Categorization. Oxford University Press, Oxford (2001)Google Scholar
  8. 8.
    Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Francisco (1993)Google Scholar
  9. 9.
    Liu, W., Williams, M.-A.: Trustworthiness of Information Sources and Information Pedigrees. In: Meyer, J.-J.C., Tambe, M. (eds.) ATAL 2001. LNCS (LNAI), vol. 2333, pp. 290–307. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  10. 10.
    Wendler, J., Gugenberger, P., Lenz, M.: CBR for Dynamic Situation Assessment in an Agent-Oriented Setting. In: ECAI (1998)Google Scholar
  11. 11.
    Wendler, J., Kaminka, G.A., Veloso, M.: Automatically Improving Team Cooperation by Applying Coordination Models (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alankar Karol
    • 1
  • Bernhard Nebel
    • 2
  • Christopher Stanton
    • 1
  • Mary-Anne Williams
    • 1
  1. 1.Faculty of Information TechnologyUniversity of TechnologySydneyAustralia
  2. 2.Institut für InformatikAlbert-Ludwigs-Universität FreiburgFreiburgGermany

Personalised recommendations