Diagnosis is widely used in many different disciplines to identify the nature and cause of a certain phenomenon. We present tL, a new logical framework able to formalise diagnostic reasoning, i.e., an hybrid learning technique based both on deduction and experiments. We use the expressiveness of Labeled Modal Logic, garnishing with temporal and statistical information a basic propositional language. We fully define syntax of formulae and relational rules between labels. After proposing examples on how tL effectively works, we sketch the main idea about the full deduction system à la Prawitz we are currently developing.

Towards a logical framework for diagnostic reasoning

M. Cristani;F. Olivieri
Membro del Collaboration Group
;
C. Tomazzoli;M. Zorzi
2018-01-01

Abstract

Diagnosis is widely used in many different disciplines to identify the nature and cause of a certain phenomenon. We present tL, a new logical framework able to formalise diagnostic reasoning, i.e., an hybrid learning technique based both on deduction and experiments. We use the expressiveness of Labeled Modal Logic, garnishing with temporal and statistical information a basic propositional language. We fully define syntax of formulae and relational rules between labels. After proposing examples on how tL effectively works, we sketch the main idea about the full deduction system à la Prawitz we are currently developing.
2018
Labeled Logic; Hybrid reasoning; Natural Deduction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/980681
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