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Speculative Constraint Processing in Multi-agent Systems

  • Ken Satoh
  • Philippe Codognet
  • Hiroshi Hosobe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2891)

Abstract

In this paper, we extend our framework of speculative computation in multi-agent systems by using default constraints. In research on multi-agent systems, handling incomplete information due to communication failure or due to other agents’ delay in communication, is a very important issue. For a solution to this problem, we previously proposed speculative computation based on abduction in the context of master-slave multi-agent systems and gave a procedure in abductive logic programming. In the proposal, a master agent prepares a default value for a yes/no question in advance and it performs speculative computation using the default without waiting for a reply to the question. This computation is effective unless the contradictory reply to the default is returned. In this paper, we formalize speculative constraint processing and propose a correct procedure for such computation so that we can handle not only yes/no questions, but also more general types of questions.

Keywords

Speculative Computation Small Room Speculative Framework Tentative Answer Constraint Logic Program 
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. [Janson91]
    Janson, S., Haridi, S.: Programming Paradigms of the Andorra Kernel Language. In: Proc. of ISLP 1991, pp. 167–186 (1991)Google Scholar
  2. [Saraswat93]
    Saraswat, V.A.: Concurrent constraint programming. Doctoral Dissertation Award and Logic Programming Series. MIT Press, Cambridge (1993)Google Scholar
  3. [Satoh00]
    Satoh, K., Inoue, K., Iwanuma, K., Sakama, C.: Speculative Computation by Abduction under Incomplete Communication Environments. In: Proc. of ICMAS 2000, pp. 263–270 (2000)Google Scholar
  4. [Smolka95]
    Smolka, G.: The Oz Programming Model. In: van Leeuwen, J. (ed.) Computer Science Today. LNCS, vol. 1000, pp. 324–343. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  5. [Yokoo98]
    Yokoo, M., Durfee, E.H., Ishida, T., Kuwabara, K.: The Distributed Constraint Satisfaction Problem: Formalization and Algorithms. TKDE 10(5), 673–685 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Ken Satoh
    • 1
  • Philippe Codognet
    • 2
  • Hiroshi Hosobe
    • 1
  1. 1.National Institute of InformaticsTokyoJapan
  2. 2.LIP6/IAUniversity of Paris 6ParisFrance

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