Efficient trajectories computing using inversibilities properties

Marie-Odile Cordier (1) , Alban Grastien (1) , Christine Largouët (1) , Yannick Pencolé (2)

1 DREAM - Diagnosing, Recommending Actions and Modelling
2 Austalian National University

A time-consuming problem encountered both in system diagnosis and planning is that of computing trajectories over a behavioral model. In order to improve the efficiency of this task, there is currently a great interest in using model-checking techniques developed within the area of computer aided verification. In this paper, we propose to represent the system as automata and we define a property called inversibility. This property is used to improve the efficiency of the search algorithm computing trajectories. We present two study cases in diagnosis and planning domains where this approach gives satisfactory results.

Domaines: Intelligence artificielle [cs.AI]

Marie-Odile Cordier, Alban Grastien, Christine Largouët, Yannick Pencolé. Efficient trajectories computing using inversibilities properties. 14th international workshop on principles of diagnosis, Jun 2003, Washington / USA. ⟨inria-00000523⟩