Multifacetted modelling and discrete event simulation
Multifacetted modelling and discrete event simulation
Reasoning about change: time and causation from the standpoint of artificial intelligence
Reasoning about change: time and causation from the standpoint of artificial intelligence
Modeling a dynamic and uncertain world I: symbolic and probabilistic reasoning about change
Artificial Intelligence
A survey on temporal reasoning in artificial intelligence
AI Communications
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Common KADS Library for Expertise Modelling
Common KADS Library for Expertise Modelling
Theory of Modelling and Simulation
Theory of Modelling and Simulation
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Gas-Turbine Condition Monitoring Using Qualitative Model-Based Diagnosis
IEEE Expert: Intelligent Systems and Their Applications
Verification and validation of the SACHEM Conceptual model
International Journal of Human-Computer Studies
Context Dependent Effects in Temporal Planning
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Modelling structures in generic space, a condition for adaptiveness of monitoring cognitive agent
Journal of Intelligent and Robotic Systems
Monitoring and alarm interpretation in industrial environments
AI Communications
Hi-index | 0.01 |
Sachem is an extensive large-scale real time knowledge-based system designed to monitor and diagnose blast furnaces. This paper aims at illustrating the way the concept of discrete event allowed the definition of a “perception-based diagnosis” approach as a recursive and holographic abstraction process of a discrete event. The example of the diagnosis of a “thermal load” phenomenon on a blast furnace is used in order to illustrate the way Sachem apply the “perception-based diagnosis” approach. Some considerations about the blast furnace and the development of Sachem are also presented in the paper to recall the complexity and the issue of the design of powerful perception systems.