In this paper, we provide our preliminary results on failure/fault analysis for an autonomous agent whose behavior is influenced by disturbances from its environment. It is assumed that failures are unobservable and only detected through some observable symptoms. Furthermore, faults may be observable directly, but the conditions leading to them are unknown a priori. Both the agent and its environment may contribute to any given failure or fault. The main results of this paper relate to the development of a diagnoser model which is built by a parallel composition of Petri net models of the underlying components. This model includes both the normative and disruptive behavior of the agent and its perception of the environment. The uncontrollability of the environment leads to a non-deterministic diagnosis behavior. The likelihood of each possible state of the agent's diagnoser is updated every time that a new controllable action is taken or new sensory information is received. At each updating, if the likelihood of a failure or fault state is higher than a specified threshold, then an alarm is raised indicating a disruptive event.

We describe here how to obtain a model for the admissible behavior of a Discrete Event System that is represented by a safe Petri Net model. The events of this Petri Net model may be controllable or uncontrollable. Also given is a sequential specification which is modeled with a special state machine. Then, using the condition and event arcs of Net ConditionlEvent Systems, a combined model of plant and specification is obtained. We use only the structure of this combined model to develop a method which gives the admissible behavior of the system. Thus, we avoid the complexity of a complete state enumeration.