Advertisement

Considerations for Real-Time Spatially-Aware Case-Based Reasoning: A Case Study in Robotic Soccer Imitation

  • Michael W. Floyd
  • Alan Davoust
  • Babak Esfandiari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5239)

Abstract

Case-base reasoning in a real-time context requires the system to output the solution to a given problem in a predictable and usually very fast time frame. As the number of cases that can be processed is limited by the real-time constraint, we explore ways of selecting the most important cases and ways of speeding up case comparisons by optimizing the representation of each case. We focus on spatially-aware systems such as mobile robotic applications and the particular challenges in representing the systems’ spatial environment. We select and combine techniques for feature selection, clustering and prototyping that are applicable in this particular context and report results from a case study with a simulated RoboCup soccer-playing agent. Our results demonstrate that preprocessing such case bases can significantly improve the imitative ability of an agent.

Keywords

Feature Selection Case Base Feature Selection Algorithm Case Representation Prototypical Case 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Smyth, B.: Case-base maintenance. In: Proceedings of the Eleventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (1998)Google Scholar
  2. 2.
    RoboCup: Robocup online (2008), http://www.robocup.org
  3. 3.
    Floyd, M.W., Esfandiari, B., Lam, K.: A case-based approach to imitating robocup players. In: Twenty-First International FLAIRS Conference, pp. 251–256 (2008)Google Scholar
  4. 4.
    Lam, K., Esfandiari, B., Tudino, D.: A scene-based imitation framework for robocup clients. In: Proceedings of the Workshop MOO at AAMAS 2006 (2006)Google Scholar
  5. 5.
    Davoust, A., Floyd, M.W., Esfandiari, B.: Use of fuzzy histograms to model the spatial distribution of objects in case-based reasoning. In: Bergler, S. (ed.) Canadian Conference on AI, pp. 72–83. Springer, Heidelberg (2008)Google Scholar
  6. 6.
    Karol, A., Nebel, B., Stanton, C., Williams, M.A.: Case based game play in the robocup four-legged league part i the theoretical model. In: RoboCup (2003)Google Scholar
  7. 7.
    Moravec, H., Elfes, A.E.: High resolution maps from wide angle sonar. In: Proceedings of the 1985 IEEE International Conference on Robotics and Automation, pp. 116–121 (1985)Google Scholar
  8. 8.
    Langner, K.: The Krislet Java Client (1999), http://www.ida.liu.se/frehe/RoboCup/Libs
  9. 9.
    Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence 97(1-2), 273–324 (1997)zbMATHCrossRefGoogle Scholar
  10. 10.
    John, G.H., Kohavi, R., Pfleger, K.: Irrelevant features and the subset selection problem. In: Proceedings of the Eleventh ICML, pp. 121–129 (1994)Google Scholar
  11. 11.
    Aha, D.W., Bankert, R.L.: A comparative evaluation of sequential feature selection algorithms. Learning from Data: AI and Statistics V, 199–206 (1996)Google Scholar
  12. 12.
    Xu, R., Wunsch, D.I.I.: Survey of clustering algorithms. IEEE Transactions on Neural Networks 16(3), 645–678 (2005)CrossRefGoogle Scholar
  13. 13.
    Bicego, M., Murino, V., Figueiredo, M.A.T.: Similarity-based clustering of sequences using hidden markov models. In: Perner, P., Rosenfeld, A. (eds.) MLDM 2003. LNCS, vol. 2734, pp. 86–95. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Dubnov, S., El-Yaniv, R., Gdalyahu, Y., Schneidman, E., Tishby, N., Yona, G.: A new nonparametric pairwise clustering algorithm based on iterative estimation of distance profiles. Mach. Learn. 47(1), 35–61 (2002)zbMATHCrossRefGoogle Scholar
  15. 15.
    Hartigan, J.A.: Clustering Algorithms. John Wiley & Sons, Inc., New York (1975)zbMATHGoogle Scholar
  16. 16.
    Berger, R., Lämmel, G.: Exploiting past experience – case-based decision support for soccer agents. In: Hertzberg, J., Beetz, M., Englert, R. (eds.) KI 2007. LNCS (LNAI), vol. 4667. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  17. 17.
    Steffens, T.: Adapting similarity measures to agent types in opponent modeling. In: Proceedings of the Workshop MOO at AAMAS 2004, pp. 125–128 (2004)Google Scholar
  18. 18.
    Ahmadi, M., Lamjiri, A.K., Nevisi, M.M., Habibi, J., Badie, K.: Using a two-layered case-based reasoning for prediction in soccer coach. In: Proceedings of the MLMTA 2003, Las Vegas, Nevada, pp. 181–185 (2003)Google Scholar
  19. 19.
    Marling, C., Tomko, M., Gillen, M., Alexander, D., Chelberg, D.: Case-based reasoning for planning and world modeling in the robocup small sized league. In: IJCAI Workshop on Issues in Designing Physical Agents for Dynamic Real-Time Environments (2003)Google Scholar
  20. 20.
    Ros, R., de Mántaras, R.L., Arcos, J.L., Veloso, M.: Team playing behavior in robot soccer: A case-based approach. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 46–60. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  21. 21.
    Wettschereck, D., Aha, D.W.: Weighting features. In: First International CBR Research and Development Conference, pp. 347–358. Springer, Berlin (1995)Google Scholar
  22. 22.
    Jarmulak, J., Craw, S., Crowe, R.: Genetic algorithms to optimise CBR retrieval. In: 5th European Workshop on Advances in CBR, pp. 136–147 (2000)Google Scholar
  23. 23.
    Maximini, K., Maximini, R., Bergmann, R.: An investigation of generalized cases. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, pp. 261–275. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  24. 24.
    Lenz, M., Burkhard, H.D.: Case retrieval nets: Basic ideas and extensions. Kunstliche Intelligenz, 227–239 (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Michael W. Floyd
    • 1
  • Alan Davoust
    • 1
  • Babak Esfandiari
    • 1
  1. 1.Department of Systems and Computer EngineeringCarleton UniversityOttawaOntario

Personalised recommendations