A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Diagnosis of large active systems
Artificial Intelligence
On the relationship between model-based debugging and program slicing
Artificial Intelligence
Diagnosis of discrete-event systems from uncertain temporal observations
Artificial Intelligence
Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems
Discrete Event Dynamic Systems
Discrete Event Dynamic Systems
Flexible diagnosis of discrete-event systems by similarity-based reasoning techniques
Artificial Intelligence
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
A diagnostic environment for automaton networks
Software—Practice & Experience
Incremental processing of temporal observations in Model-Based Reasoning
AI Communications - Model-Based Systems
Temporal decision trees: model-based diagnosis of dynamic systems on-board
Journal of Artificial Intelligence Research
Exploiting independence in a decentralised and incremental approach of diagnosis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Chronicle recognition improvement using temporal focusing and hierarchization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
| Hi-index | 0.00 |
Model-based diagnosis of discrete event systems (DESs) is more and more active in artificial intelligence. However, there has been always a very restrictive assumption in the previous works that the model of a given DES is complete, including all nominal behaviors and all possible failure behaviors of the system. In order to relax this so restrictive assumption, in this paper, model-based diagnosis of a DES with an incomplete system model is investigated. A new concept of “P-synchronization product” of finite state automata is proposed, by which the P-diagnosis of the DES with an incomplete system model is easily put forward. It is also shown that the traditional synchronization product of finite state automata can be seen as a special situation of P-synchronization product. In addition, an ideal heuristic way from theoretical view to improve the P-synchronization product is discussed as well.