Marie-Odile Cordier and Alban Grastien Exploiting independence in a decentralised and incremental approach of diagnosis , DX'06 (17th International workshop on principles of Diagnosis) , Burgos , 61--69 , 2006 , Document Abstract It is now well-known that the size of the model is the bottleneck when using model-based approaches to diagnose complex systems. To answer this problem, decentralized/distributed approaches have been proposed. The global system model is described through its component models as a set of automata and the global diagnosis is computed from the component diagnoses (also called local diagnoses). Another problem, which is far less considered, is the size of the diagnosis itself. However, it can also be huge enough, especially when dealing with uncertain observations. It is why we recently proposed to slice the observation flow into temporal windows and to compute the diagnosis in an incremental way from these diagnosis slices. In this context, we define in this paper two independence properties (transition and state independence) and we show their relevance to get a tractable representation of diagnosis. The diagnosis slices are economically represented by a set of transition-independent diagnoses and its associated set of abstract descriptions, from which the set of final states and the trajectories of the global diagnosis can be easily retrieved. To illustrate the impact on the diagnosis size, experimental results on a toy example are given. This web site is maintained by René Quiniou using the Weave system from the Caravel project: http://www-caravel.inria.fr. Last modification: 10-07-2011 09:54:25