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

Automatic Web services composition can be achieved by 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, we 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 hence be able to find more than one plan, taking both functional and non-functional properties into account. Furthermore, an evaluation method to choose the optimal plan and some 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 the approach to a realistic case study.