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Summary

This study introduces a novel evidential reasoning approach, integrating arguments, scenarios, and probabilities within a formal case model framework. This method bridges qualitative and quantitative analysis for rational case assessment.

Keywords:
Argumentation modelsCase analysisCriminal lawEvidential reasoningNarrative modelsProbabilistic modelsRational proof

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Area of Science:

  • Decision Analysis
  • Logic and Reasoning
  • Forensic Science

Background:

  • Existing literature on rational analysis of cases employs diverse theoretical perspectives.
  • Current approaches often combine arguments, scenarios, and probabilities in varied ways.
  • A need exists for a unified framework to connect qualitative and quantitative analytical styles.

Purpose of the Study:

  • To develop and present a novel theoretical perspective on evidential reasoning.
  • To formally integrate arguments, scenarios, and probabilities into a single modeling approach.
  • To investigate the connection between qualitative and quantitative analytical methods.

Main Methods:

  • Utilized the logical formalism of case models, where cases represent combinations of evidence and events.
  • Employed an ordering relation to structure these cases.
  • Represented the ordering relation using a probability function within the evidential reasoning context.

Main Results:

  • Demonstrated a formal modeling approach that connects arguments, scenarios, and probabilities.
  • Showcased how case models can bridge qualitative and quantitative analytic styles.
  • Established a framework where an ordering relation is simultaneously qualitative and probabilistic.

Conclusions:

  • The proposed evidential reasoning perspective offers a unified approach to case analysis.
  • Case models provide a powerful tool for integrating diverse analytical methods.
  • This framework facilitates a more comprehensive understanding of complex evidential scenarios.