Une approche multi-agent pour la conception de systèmes d'intelligence ambiante : un modèle formel intégrant planification et apprentissage

摘要

This work presents a concrete software architecture dedicated to ambient intelligence (AmI) features and requirements. The proposed behavioral model, called Higher-order Agent (HoA) captures the evolution of the mental representation of the agent and the one of its plan simultaneously. Plan expressions are written and composed using a formal algebraic language, namely AgLOTOS, so that plans are built automatically and on the fly, as a system of concurrent processes. Due to the compositional structure of AgLOTOS expressions, the updates of sub-plans are realized automatically accordingly to the revising of intentions, hence maintaining the consistency of the agent. Based on a specific semantics, a guidance service is also proposed to assist the agent in its execution. This guidance allows to improve the satisfaction of the agent's intentions with respect to the possible concurrent plans and the current context of the agent. Adopting the idea that "location" and "time" are key stones information in the activity of the agent, we show how to enforce guidance by ordering the different possible plans. As a major contribution, we demonstrate two original utility functions that are designed from the past-experiences of the action executions, and that can be combined accordingly to the current balance policy of the agent. A use case scenario is developed to show how the agent can act, even if it suffers from unexpected changes of contexts, it does not have many experiences and whose past experiences reveals some failure cases.