Abstract
Sequential decision making techniques have been applied to solve problems of Cloud service selection and composition. However, existing researches rarely focus on studying Cloud service compositions in a partially observable multiagent interactive environment. In this paper, we propose an interactive service composition model I-SerCom that applies the Interactive Partially Observable Markov Decision Process (I-POMDP) to help service buyers make sequential service selection policies. I-SerCom enables buyers make decisions by considering both changes of states of service marketplaces and an evolution of the intention of other involved agents. We use Interactive Influence Diagram (I-DID) to graphically represent the model. The I-DID factorization makes the model description more explicit and simplifies the model solving process. We use a case study of cloud service selection to present the process of I-SerCom, and conclude that I-SerCom is an efficient method for service composition.
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