Context Optimization of AI planning for Services Composition
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With the growing emergence of ubiquitous computing and networked systems, ubiquitous robotics is becoming an active research domain. The issue of services composition to offer seamless access to a variety of complex services has received widespread attention in recent years. The majority of the proposed approaches have been inspired from the research undertaken jointly on Workflow and AI-based classical planning techniques. However, the traditional AI-based methods assume that the environment is static and the invocation of the services is deterministic. In ubiquitous robotics, services composition is a challenging issue when the execution environment and services are dynamic and the knowledge about their state and context is uncertain. The services composition requires taking into account the parameters of quality of service (QoS) to adapt the composed service to context of the user and the environment, in particular, dealing with failures such as: service invocation failures, network disconnection, sensor failures, context change due to mobility of objects (robots, sensors, etc.), service discovery failures and service execution failures. In this paper, we present a framework which gives ubiquitous robotic system the ability to dynamically compose and deliver ubiquitous services, and to monitor their execution. The main motivation behind the use of services composition is to decrease time and costs to develop integrated complex applications using robots by transforming them from a single task issuer to smart services provider and human companion, without rebuilding each time the robotic system. To address these new challenges, we propose in this paper a new framework for services composition and monitoring, including QoS estimation and Bayesian learning model to deal with the dynamic and uncertain nature of the environment. This framework includes three levels: abstract plan construction, plan execution, and services discovery and re-composition. This approach is tested under USARSim simulator on a prototype of ubiquitous robotic services for assisting an elderly person at home. The obtained results from extensive tests demonstrate clearly the feasibility and efficiency of our approach.