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Using Markov Decision Process Model with Logic Scoring of Preference Model to Optimize HTN Web Services Composition

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  • Jiuyun Xu

    (China University of Petroleum, Shandong, China, State key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications), Beijing, China)

  • Kun Chen

    (China University of Petroleum, Shandong, China)

  • Stephan Reiff-Marganiec

    (University of Leicester, UK)

Abstract

Automatic Web services composition can be achieved using AI planning techniques. HTN planning has been adopted to handle the OWL-S Web service composition problem. However, existing composition methods based on HTN planning have not considered the choice of decompositions available to a problem, which can lead to a variety of valid solutions. In this paper, the authors propose a model of combining a Markov decision process model and HTN planning to address Web services composition. In the model, HTN planning is enhanced to decompose a task in multiple ways and find more than one plan, taking into account both functional and non-functional properties. Furthermore, an evaluation method to choose the optimal plan and experimental results illustrate that the proposed approach works effectively. The paper extends previous work by refining a number of aspects of the approach and applying it to a realistic case study.

Suggested Citation

  • Jiuyun Xu & Kun Chen & Stephan Reiff-Marganiec, 2011. "Using Markov Decision Process Model with Logic Scoring of Preference Model to Optimize HTN Web Services Composition," International Journal of Web Services Research (IJWSR), IGI Global, vol. 8(2), pages 53-73, April.
    • Handle: RePEc:igg:jwsr00:v:8:y:2011:i:2:p:53-73
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