Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Diagnosis of large active systems
Artificial Intelligence
Model checking
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
Process algebras for systems diagnosis
Artificial Intelligence
Back to the Future for Consistency-Based Trajectory Tracking
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
All from One, One for All: on Model Checking Using Representatives
CAV '93 Proceedings of the 5th International Conference on Computer Aided Verification
Linear Time, Branching Time and Partial Order in Logics and Models for Concurrency, School/Workshop
A model-based approach to reactive self-configuring systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Diagnosis of a class of distributed discrete-event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On-line monitoring of plan execution: A distributed approach
Knowledge-Based Systems
A diagnostic environment for automaton networks
Software—Practice & Experience
Diagnosis of Discrete Event Systems Using Decentralized Architectures
Discrete Event Dynamic Systems
Incremental processing of temporal observations in Model-Based Reasoning
AI Communications - Model-Based Systems
Call Forwarding-Based Active Probing for POTS Fault Isolation
Journal of Network and Systems Management
Primary and secondary diagnosis of multi-agent plan execution
Autonomous Agents and Multi-Agent Systems
Model-Based Diagnosis of Discrete Event Systems with an Incomplete System Model
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Chronicles for On-line Diagnosis of Distributed Systems
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Observation-Subsumption Checking in Similarity-Based Diagnosis of Discrete-Event Systems
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Local Consistency and Junction Tree for Diagnosis of Discrete-Event Systems
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Monitoring the Execution of a Multi-Agent Plan: Dealing with Partial Observability
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Dependable Monitoring of Discrete-Event Systems with Uncertain Temporal Observations
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
A spectrum of symbolic on-line diagnosis approaches
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A framework for decentralized qualitative model-based diagnosis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Exploiting independence in a decentralised and incremental approach of diagnosis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Scalable diagnosability checking of event-driven systems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A Decentralised Symbolic Diagnosis Approach
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Diagnosing Process Trajectories Under Partially Known Behavior
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Hi-index | 0.00 |
We address the problem of diagnosing large discrete event systems. Given a flow of observations from the system, the goal is to explain these observations on-line by identifying and localising possible failures and their consequences across the system. Model-based diagnosis approaches deal with this problem but, apart very recent proposals, either they require the computation of a global model of the system which is not possible with large discrete event systems, or they cannot perform on-line diagnosis. The contribution of this paper is the description and the implementation of a formal framework for the on-line decentralised diagnosis of such systems, framework which is based on the "divide and conquer" principle and does not require the global model computation. This paper finally describes the use of this framework in the monitoring of a real telecommunication network.