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An Argumentation Based Approach for Dynamic Service Composition in Ambient Intelligence Environments
The ability to efficiently select and compose heterogeneous services at runtime is an important challenge for end-user applications. Several approaches are proposed for dynamic service composition in distributed environments, specifically multi-agents approach that appears as a powerful and promising solution. However, there is no way for these approaches to verify or justify the success and correctness of the composition process. Moreover, autonomous agents need a high capacity of reasoning and interaction to achieve the composition in rapidly changing environments. These aspects are extremely important in Ambient Intelligence environments, which are characterized by numerous heterogeneous and variable devices when security functioning takes a high priority. In this paper, we propose a multi-agent approach for dynamic service composition in Ambient Intelligence environments. In our approach, agents use argumentation as a reasoning process for service selection and composition. In addition, agents are able to learn new compositions of services. The benefit of our approach is that autonomous agents are able to explain and justify the composite services they construct and ensure that these compositions fulfill the user requirements.
Multi-agent systems, logical reasoning, argumentation, service composition, service selection, ambient intelligence environment.
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