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Resource-dependent contextual planning in AmI

Abstract : When we consider ambient intelligence (AmI) environments, contextual planning for multiple agents requires efficient management of resources in order to deploy multi-agent plans. We propose a contextual planning framework to be used by agents in such environments. The proposed framework covers the entire cycle from modeling, multi-agent contextual planning, and deployment of generated plans while ensuring concurrent access and sharing of physical resources. For efficient and effective management of resources, the framework includes a resource management layer. This layer works as a service that provides the virtualization and registration of environments and devices informing the resources availability. The added value of this framework resides in formalizing resource-dependent contextual states in order to allow existing physical resources to be properly perceived as part of the context. Consequently, it allows for plan feasibility to be verified according to any eventual resources requirements related to the deployed plans. The paper goes on to present a proof of concept implementing a scenario based on real-world conditions. In that, we extrapolate the internal execution and monitoring mechanisms that should be required in the case of the framework practical application.
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https://hal.sorbonne-universite.fr/hal-02892155
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Submitted on : Tuesday, July 7, 2020 - 1:07:28 PM
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Arthur Casals, Amal El Fallah-Seghrouchni, Anarosa Alves Franco Brandão, Carlos Pantoja, Jose Viterbo. Resource-dependent contextual planning in AmI. Procedia Computer Science, Elsevier, 2019, 151, pp.485-492. ⟨10.1016/j.procs.2019.04.066⟩. ⟨hal-02892155⟩

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