Next: About this document ...
Up: In C. Freksa, ed.,
Previous: Acknowledgments
Chaitin:87
G.J. Chaitin.
Algorithmic Information Theory.
Cambridge University Press, Cambridge, 1987.
Kolmogorov:65
A.N. Kolmogorov.
Three approaches to the quantitative definition of information.
Problems of Information Transmission, 1:1--11, 1965.
Levin:74
L.~A. Levin.
Laws of information (nongrowth) and aspects of the foundation of
probability theory.
Problems of Information Transmission, 10(3):206--210, 1974.
Levin:84
L.~A. Levin.
Randomness conservation inequalities: Information and independence in
mathematical theories.
Information and Control, 61:15--37, 1984.
Schmidhuber:97ssa
J.~Schmidhuber, J.~Zhao, and N.~Schraudolph.
Reinforcement learning with self-modifying policies.
In S.~Thrun and L.~Pratt, editors, Learning to learn, pages
293--309. Kluwer, 1997.
Schmidhuber:97bias
J.~Schmidhuber, J.~Zhao, and M.~Wiering.
Shifting inductive bias with success-story algorithm, adaptive
Levin search, and incremental self-improvement.
Machine Learning, 28:105--130, 1997.
Shannon:48
C.~E. Shannon.
A mathematical theory of communication (parts I and II).
Bell System Technical Journal, XXVII:379--423, 1948.
Solomonoff:64
R.J. Solomonoff.
A formal theory of inductive inference. Part I.
Information and Control, 7:1--22, 1964.
Wolpert:96
D.~H. Wolpert.
The lack of a priori distinctions between learning algorithms.
Neural Computation, 8(7):1341--1390, 1996.
Juergen Schmidhuber
1999-03-15
Related links: In the beginning was the code! - Zuse's thesis - Algorithmic Theories of Everything - Generalized Algorithmic Information - Speed Prior - The New AI