Table of Contents
The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions(Proc. COLT 2002, based on quant-ph/0011122, 2000)
Foundations of inductive inference
Optimal Inductive Inference
Bayesmix: Sharp Loss Bounds M. Hutter (on my SNF grant; IJFCS / ECML / ICML 2001)
Universal Mix
Problem: Universal M(x) not recursive
Ressource Postulate
Fastest way of making data
FAST & universal search (II)
Postulate+ FAST= Speed Prior S
S through Algorithm GUESS
S-based inductive inference
Approximating S through AS
S-based inductive inference II
S-based Inference III
Example: discrete pseudorandom universe (skip this if you don’t care for applications)
Consequences for physics etc (ignore this if you don’t care for applications)
Summary
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Author: J. Schmidhuber
Email: juergen@idsia.ch
Home Page: http://www.idsia.ch/~juergen
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