An On-Line Multi-CBR Agent Dispatching Algorithm | Soft Computing Skip to main content
Log in

An On-Line Multi-CBR Agent Dispatching Algorithm

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Case-based reasoning (CBR) is an effective and fast problem-solving methodology, which solves new problems by remembering and adaptation of past cases. With the increasing requests for useful references for all kinds of problems and from different locations, keeping a single CBR system seems to be outdated and not practical. Multi-CBR agents located in different places are of great support to fast meet these requests. In this paper, the architecture of a multi-CBR agent system is proposed, where each CBR agent locates at different places, and is assumed to have the same ability to deal with new problem independently. When requests in a request queue are coming one by one from different places, we propose a new policy of agent dispatching to satisfy the request queue. Throughout the paper, we assume that the system must solve the coming request by considering only past requests. In this context, the performance of traditional greedy algorithms is not satisfactory. We apply a new but simple approach – competitive algorithm for on-line problem (called ODAL) to determine the dispatching policy to keep comparative low cost. The corresponding on-line dispatching algorithm is proposed and the competitive ratio is given. Based on the competitive algorithm, the dispatching of multi-CBR agents is optimized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Plaza E, Ontañòn S (2001) Ensemble case-based reasoning: collaboration policies for multiagent cooperative CBR. In: Proceedings of ICCBR-01, pp 437–451

  2. Ontañon S, Plaza E (2001) Learning when to collaborate among learning agents. In: Proceedings of machine learning: EMCL-01, pp 394–405

  3. Papadimitriou CH, Yannakakis M (1991) Shortest paths without a map. Theor Comput Sci 84:127–150

    Article  MATH  MathSciNet  Google Scholar 

  4. Chrobak M, larmore L (1992) The server problem and on-line games. DIMACS Ser Discrete Math Theor Comput Sci 7:11–64

    MATH  MathSciNet  Google Scholar 

  5. Chekuri C, Motwani R, Natarajan B, Stein C (2001) Approximation techniques for average completion time scheduling. SIAM J Comput 31:146–166

    Article  MATH  MathSciNet  Google Scholar 

  6. Manasse MS, McGeoch LA, Sleator DD (1990) Competitive algorithms for server problems. J Algorithms 11:208–230

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yan Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, Y., Wang, XZ. & Ha, MH. An On-Line Multi-CBR Agent Dispatching Algorithm. Soft Comput 11, 391–395 (2007). https://doi.org/10.1007/s00500-006-0094-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-006-0094-2

Keywords

Navigation