A LEARNING-THEORETIC CHARACTERISATION OF MARTIN-LÖF RANDOMNESS AND SCHNORR RANDOMNESS

DOI10.1017/s175502031900042xOpenAlexW2986239583MaRDI QIDQ6193396

Francesca Zaffora Blando

Publication date: 16 March 2024

Published in: The Review of Symbolic Logic (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s175502031900042x

zbMATH Keywords

algorithmic randomnessformal learning theory

Mathematics Subject Classification ID

Computational learning theory (68Q32) Algorithmic information theory (Kolmogorov complexity, etc.) (68Q30) Algorithmic randomness and dimension (03D32)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Zufälligkeit und Wahrscheinlichkeit. Eine algorithmische Begründung der Wahrscheinlichkeitstheorie. (Randomness and probability. An algorithmic foundation of probability theory)
• L1-Computability, Layerwise Computability and Solovay Reducibility
• RECOGNIZING STRONG RANDOM REALS
• Probabilities over rich languages, testing and randomness
• On the Length of Programs for Computing Finite Binary Sequences
• A unified approach to the definition of random sequences
• The definition of random sequences
• Language identification in the limit
• A formal theory of inductive inference. Part II

This page was built for publication: A LEARNING-THEORETIC CHARACTERISATION OF MARTIN-LÖF RANDOMNESS AND SCHNORR RANDOMNESS