Towards the use of Situation Hierarchies for supporting Decision Making: A Formal Lattice-Based Approach

Franco Giustozzi (1) , Julien Saunier (1) , Cecilia Zanni-Merk (1)

1 MIND - LITIS - Equipe Multi-agent, Interaction, Décision

Monitoring is a critical task to manage modern applications using cyber-physical systems such as in healthcare, environmental monitoring, water and energy distribution or Industry 4.0. Its main goal is the optimization of the equipment use, the prediction or avoidance of failures, and the change in the operating modes of the system according to both the system goals and its current condition. The abnormal situations that could lead to failures can have different levels of severity, and can be nested in different ways. In this context, this paper proposes a method to build a lattice, ordering those situations depending on the constraints they rely on. This lattice represents a road-map of all the situations that can be reached from a given one, desirable or undesirable. This helps in decision support, by allowing the identification of the actions that can be taken to correct the abnormality avoiding in this way the interruption of the system processes.

Mots clés: Knowledge Representation; Lattice Theory; Industry 4.0

Domaines: Intelligence artificielle [cs.AI]

Franco Giustozzi, Julien Saunier, Cecilia Zanni-Merk. Towards the use of Situation Hierarchies for supporting Decision Making: A Formal Lattice-Based Approach. In Proceedings of the 14th International Rule Challenge (RuleML+RR 2020) as part of Declarative AI 2020, Jun 2020, Oslo, Norway. pp.73-86. ⟨hal-02909950⟩