Abstract: A method is provided for managing decisions between a central manager and at least one terminal in an architecture of networks distributed and prioritized according to N levels, with N?2. The central manager is included in a level of rank N. The terminal is included in a level of rank 1. The method includes a step of distributing a decision tree constructed by the central manager and supported by the architecture.

Abstract: A method is provided for managing decisions between a central manager and at least one terminal in an architecture of networks distributed and prioritized according to N levels, with N?2. The central manager is included in a level of rank N. The terminal is included in a level of rank 1. The method includes a step of distributing a decision tree constructed by the central manager and supported by the architecture.

Abstract: An automatic method for learning frequent chronicles in an alarm log of a dynamic system for supervision of the system, and a learning system for using the method in a supervision system. According to the method, in an alarm log, alarm sequences are selected and then grouped in groups of similar sequences. Alarms of the groups are then used to produce partial logs. Frequent chronicles are then learned on each transmitted partial log and the partial set of frequent chronicles is determined. Then a set of chronicles in the log is formed with chronicles of the various partial sets.

Abstract: In a method of recognition of a chronicle from a set of possible chronicles, each of said chronicles consists of a set of events related to one another by pre-determined conditions, said events comprising elementary events and complex events corresponding to a specific combination of at least two elementary events. The method comprising the following steps: obtaining a series of elementary events; determining at least one chronicle, called a presumed chronicle, that meets at least certain of said conditions interrelating said elementary events, from among said set of possible chronicles; and for each of said presumed chronicles, identifying at least one complex event that has to be present in said presumed chronicle; verifying the presence of said complex event from corresponding elementary events; confirming the recognition of said chronicle if said complex event or events are present; so that only the complex events necessary for said recognition are computed.

Abstract: An automatic method for learning frequent chronicles in an alarm log of a dynamic system for supervision of the system, and a learning system for using the method in a supervision system. According to the method, in an alarm log, alarm sequences are selected and then grouped in groups of similar sequences. Alarms of the groups are then used to produce partial logs. Frequent chronicles are then learned on each transmitted partial log and the partial set of frequent chronicles is determined. Then a set of chronicles in the log is formed with chronicles of the various partial sets.