Published in Volume XXIX, Issue 1, 2019, pages 1–58, doi: 10.7561/SACS.2019.1.1

Authors: J.A. Bergstra

Abstract

Bayesian inference as applied in a legal setting is about belief transfer and involves a plurality of agents and communication protocols. A forensic expert (FE) may communicate to a trier of fact (TOF) first its value of a certain likelihood ratio with respect to FE’s belief state as represented by a probability function on FE’s proposition space.

Subsequently FE communicates its recently acquired confirmation that a certain evidence proposition is true. Then TOF performs likelihood ratio transfer mediated reasoning thereby revising their own belief state.

The logical principles involved in likelihood transfer mediated reasoning are discussed in a setting where probabilistic arithmetic is done within a meadow, and with Adams conditioning placed in a central role.

Keywords: Boolean algebra, meadow, likelihood ratio, Adams conditioning, Bayesian conditioning, imprecise probabilities.

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Bibtex

@article{sacscuza:bergstra2019aclrtmi,
  title={Adams Conditioning and Likelihood Ratio Transfer Mediated Inference},
  author={J. A. Bergstra},
  journal={Scientific Annals of Computer Science},
  volume={29},
  number={1},
  organization={Alexandru Ioan Cuza University, Ia\c si, Rom\^ania},
  year={2019},
  pages={1–58},
  publisher={Alexandru Ioan Cuza University Press, Ia\c si},
  doi={10.7561/SACS.2019.1.1}
}