Advertisement

Agent Strategy Generation by Rule Induction in Predator-Prey Problem

  • Bartłomiej Śnieżyński
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5545)

Abstract

This paper contains a proposal of application of rule induction for generating agent strategy. This method of learning is tested on a predator-prey domain, in which predator agents learn how to capture preys. We assume that proposed learning mechanism will be beneficial in all domains, in which agents can determine direct results of their actions. Experimental results show that the learning process is fast. Multi-agent communication aspect is also taken into account. We can show that in specific conditions transferring learned rules gives profits to the learning agents.

Keywords

multi-agent systems rule induction machine learning 

References

  1. 1.
    Stone, P., Veloso, M.: Multiagent systems: A survey from a machine learning perspective. Autonomous Robots 8, 345–383 (2000)CrossRefGoogle Scholar
  2. 2.
    Panait, L., Luke, S.: Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems 11 (2005)CrossRefGoogle Scholar
  3. 3.
    Tan, M.: Multi-agent reinforcement learning: Independent vs. cooperative agents. In: Proceedings of the Tenth International Conference on Machine Learning, pp. 330–337. Morgan Kaufmann, San Francisco (1993)Google Scholar
  4. 4.
    Haynes, T., Sen, I.: Evolving behavioral strategies in predators and prey. In: Adaptation and Learning in Multiagent Systems, pp. 113–126. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  5. 5.
    Giles, C.L., Jim, K.-C.: Learning communication for multi-agent systems. In: WRAC, pp. 377–392 (2002)Google Scholar
  6. 6.
    Gehrke, J.D., Wojtusiak, J.: Traffic prediction for agent route planning. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part III. LNCS, vol. 5103, pp. 692–701. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Sugawara, T., Lesser, V.: On-line learning of coordination plans. In: Proceedings of the 12th International Workshop on Distributed Artificial Intelligence, pp. 335–345, 371–377 (1993) Google Scholar
  8. 8.
    Airiau, S., Padham, L., Sardina, S., Sen, S.: Incorporating learning in bdi agents. In: Proceedings of the ALAMAS+ALAg Workshop (May 2008)Google Scholar
  9. 9.
    Śnieżyński, B.: Resource management in a multi-agent system by means of reinforcement learning and supervised rule learning. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2007. LNCS, vol. 4488, pp. 864–871. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Russell, S., Norvig, P.: Artificial Intelligence – A Modern Approach. Prentice-Hall, Englewood Cliffs (1995)zbMATHGoogle Scholar
  11. 11.
    Sardinha, J., Garcia, A., Milidi, R., Lucena, C.: The agent learning pattern. In: Fourth Latin American Conference on Pattern Languages of Programming, SugarLoafPLoP 2004, Brazil (2004)Google Scholar
  12. 12.
    Śnieżyński, B.: An architecture for learning agents. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008, Part III. LNCS, vol. 5103, pp. 722–730. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Wojtusiak, J.: AQ21 User’s Guide. Reports of the Machine Learning and Inference Laboratory, MLI 04-3. George Mason University, Fairfax, VA (2004)Google Scholar
  14. 14.
    Michalski, R.S., Larson, J.: Aqval/1 (aq7) user’s guide and program description. Technical Report 731, Department of Computer Science, University of Illinois, Urbana (June 1975)Google Scholar
  15. 15.
    Majumdar, A., Tarau, P., Sowa, J.: Prologix: Users guide. Technical report, VivoMind LLC (2004)Google Scholar
  16. 16.
    Śnieżyński, B., Koźlak, J.: Learning in a multi-agent approach to a fish bank game. In: Pěchouček, M., Petta, P., Varga, L.Z. (eds.) CEEMAS 2005. LNCS, vol. 3690, pp. 568–571. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  17. 17.
    Pfau, J., Śnieżyński, B.: Comparison of reinforcement and supervised learning in the predator prey game (2008) (unpublished)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Bartłomiej Śnieżyński
    • 1
  1. 1.Department of Computer ScienceAGH University of Science and TechnologyKrakówPoland

Personalised recommendations