From Distinguishability to Information
This paper explains how observations change the probabilities assigned to possible states and how information can be understood as a reduction in uncertainty. A simple example introduces Bayesian updating and distinguishes the assessment of evidence from the choice of an action. Further examples introduce the bit and Shannon entropy, explain why repeated observations need not provide independent evidence, and clarify why the amount of information does not by itself establish truth or meaning.
Authors
- Michael Shanidze
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-08
- DOI
- https://doi.org/10.5281/zenodo.24060044
- Primary Topic
- Bayesian Modeling and Causal Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00