Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Consistency-based diagnosis concerns using a model of the structure and behaviour of a system in order to analyse whether or not the system is malfunctioning. A ll-known limitation of consistency-based diagnosis is that it is unable to cope with uncertainty. Uncertainty reasoning is nowadays done using Bayesian networks. In this field, a conflict measure has been introduced to detect conflicts beten a given probability distribution and associated data.#R##N##R##N#,  use a probabilistic theory to represent logical diagnostic systems and show that in this theory  are able to determine consistent and inconsistent states as traditionally done in consistency-based diagnosis. Furthermore,  analyse how the conflict measure in this theory offers a way to favour particular diagnoses above others. This enables us to add uncertainty reasoning to consistency-based diagnosis in a seamless fashion.
['Ildikó Flesch', 'Peter J. F. Lucas', 'Theo P. van der Weide']
I am writing a research paper on a idea Conflict-based diagnosis: adding uncertainty to model-based diagnosis
[{"from": "human", "value": "I am writing a research paper on a idea Conflict-based diagnosis: adding uncertainty to model-based diagnosis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Consistency-based diagnosis concerns using a model of the structure and behaviour of a system in order to analyse whether or not the system is malfunctioning. A ll-known limitation of consistency-based diagnosis is that it is unable to cope with uncertainty. Uncertainty reasoning is nowadays done using Bayesian networks. In this field, a conflict measure has been introduced to detect conflicts beten a given probability distribution and associated data.#R##N##R##N#,  use a probabilistic theory to represent logical diagnostic systems and show that in this theory  are able to determine consistent and inconsistent states as traditionally done in consistency-based diagnosis. Furthermore,  analyse how the conflict measure in this theory offers a way to favour particular diagnoses above others. This enables us to add uncertainty reasoning to consistency-based diagnosis in a seamless fashion."}]