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This encyclopedic article gives a mini-introduction into the theory of universal learning, founded by Ray Solomonoff in the 1960s and significantly developed and extended in the last decade.
A formal theory of inductive inference: Parts 1 and 2
R. J. Solomonoff · 1964
Earlier work this paper cites.
A. K. Zvonkin and L. A. Levin · 1970
Earlier work this paper cites.
Complexity-based induction systems: Comparisons and convergence theorems
R. J. Solomonoff · 1978
Earlier work this paper cites.
No free lunch theorems for optimization
D. H. Wolpert and W. G. Macready · 1997
Earlier work this paper cites.
Hierarchies of generalized Kolmogorov complexities and nonenumerable universal measures computable in the limit
J. Schmidhuber · 2002
Earlier work this paper cites.
Clustering by compression
R. Cilibrasi and P. M. B. Vitányi · 2005
Cited alongside, same era.
Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability
M. Hutter · 2005
Cited alongside, same era.
Human knowledge compression prize, 2006
M. Hutter · 2006
Cited alongside, same era.
Universal search
M. Gaglio · 2007
Cited alongside, same era.
The Minimum Description Length Principle
P. D. Grünwald · 2007
Later among the works it cites.
On universal prediction and Bayesian confirmation
M. Hutter · 2007
Later among the works it cites.
An Introduction to Kolmogorov Complexity and its Applications
M. Li and P. M. B. Vitányi · 2008
Later among the works it cites.
Reinforcement learning via AIXI approximation
J. Veness, K. S. Ng, M. Hutter, and D. Silver · 2010
Later among the works it cites.
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