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Multi-agent Cooperation: A Description Logic View

  • Jiewen Luo
  • Zhongzhi Shi
  • Maoguang Wang
  • He Huang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4078)

Abstract

In this paper we propose dynamic description logic for formalizing multi-agent cooperation process with a clearly defined syntax and semantics. By combining the features of knowledge representation and reasoning of description logic and action theory for multi-agent interaction, our logic is effective and significant both for static and dynamic environment. On the static side, we employ description logic for the representation and reasoning of beliefs and goals. On the dynamic side, we adopt the object-oriented method to describe actions. The description of each action is composed of models, preconditions and effects. It can reflect the real changes of the world and is very suitable for belief revision and action planning. Based on our logic, we investigate how to form joint goal for multi-agent cooperation. In particular, we propose an effective dynamic planning algorithm for scheduling sub goals, which is greatly crucial for coordinating multi-agent behaviors.

Keywords

Description Logic Belief Revision Belief Base Action Description Dynamic Planning 
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.

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References

  1. 1.
    Levesque, H.J., Cohen, P.R., Nunes, J.H.T.: On acting together. In: Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI 1990), Boston, MA, pp. 94–99 (1990)Google Scholar
  2. 2.
    Baader, W.N.: Basic description logic. In: Baader, F., et al. (eds.) The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2002)Google Scholar
  3. 3.
    Baral, C., Gelfond, M., Provetti, A.: Reasoning about actions: Laws, Observations and Hypotheses. Journal of Logic Programming 31, 201–244 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Baral, C., Gelfond, M.: Reasoning agents in dynamic domains. In: Minker, J. (ed.) Logic Based Artificial Intelligence. Kluwer, Dordrecht (2000)Google Scholar
  5. 5.
    Baral, C., Zhang, Y.: On the semantics of knowledge update. In: Proceedings of IJCAI 2001, pp. 97–102 (2001)Google Scholar
  6. 6.
    Hewitt, C.: Offices are open system. ACM transactions on Office information systems 4(3), 271–287 (1986)CrossRefGoogle Scholar
  7. 7.
    Halpern, J.Y., Moses, Y.: A guide to the modal logics of knowledge and belief: preliminary draft. In: Proceedings IJCAI 1985, Los Angeles, CA, pp. 480–490 (1985)Google Scholar
  8. 8.
    Cohen, P.R., Levesque, H.J.: Intention is choice with commitment. Artificial intelligence 42(3) (1990)Google Scholar
  9. 9.
    Wooldridge, M., Jennings, N.R.: Formalizing the Cooperative Problem Solving Process. In: Readings in Agents, pp. 430–440. Morgan Kaufmann, San Francisco (1997)Google Scholar
  10. 10.
  11. 11.
    Dong Mingkai Research on Dynamic Description Logic for Intelligent Agent; PhD thesis, Chinese Academy of Sciences (2003)Google Scholar
  12. 12.
    Intelligence science website, http://www.intsci.ac.cn
  13. 13.
    Description Logics website, http://dl.kr.org/
  14. 14.
    Zhongzhi, S.: Intelligent Agent and Its application. China Science Press (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jiewen Luo
    • 1
    • 2
  • Zhongzhi Shi
    • 1
  • Maoguang Wang
    • 1
    • 2
  • He Huang
    • 1
    • 2
  1. 1.Institute of Computing TechnologyChinese Academy of SciencesChina
  2. 2.Graduate School of Chinese Academy of SciencesBeijingP.R. China

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