Book contents
- Frontmatter
- Contents
- Preface
- 1 Key developments in algorithmic randomness
- 2 Algorithmic randomness in ergodic theory
- 3 Algorithmic randomness and constructive/computable measure theory
- 4 Algorithmic randomness and layerwise computability
- 5 Relativization in randomness
- 6 Aspects of Chaitin’s Omega
- 7 Biased algorithmic randomness
- 8 Higher randomness
- 9 Resource bounded randomness and its applications
- Index
3 - Algorithmic randomness and constructive/computable measure theory
Published online by Cambridge University Press: 07 May 2020
- Frontmatter
- Contents
- Preface
- 1 Key developments in algorithmic randomness
- 2 Algorithmic randomness in ergodic theory
- 3 Algorithmic randomness and constructive/computable measure theory
- 4 Algorithmic randomness and layerwise computability
- 5 Relativization in randomness
- 6 Aspects of Chaitin’s Omega
- 7 Biased algorithmic randomness
- 8 Higher randomness
- 9 Resource bounded randomness and its applications
- Index
Summary
This is a survey of constructive and computable measure theory with an emphasis on the close connections with algorithmic randomness. We give a brief history of constructive measure theory from Brouwer to the present, emphasizing how Schnorr randomness is the randomness notion implicit in the work of Brouwer, Bishop, Demuth, and others. We survey a number of recent results showing that classical almost everywhere convergence theorems can be used to characterize many of the common randomness notions including Schnorr randomness, computable randomness, and Martin-Löf randomness. Last, we go into more detail about computable measure theory, showing how all the major approaches are basically equivalent (even though the definitions can vary greatly).
Keywords
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- Information
- Algorithmic RandomnessProgress and Prospects, pp. 58 - 114Publisher: Cambridge University PressPrint publication year: 2020
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