next up previous
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

Related links: In the beginning was the code! - Zuse's thesis - Algorithmic Theories of Everything - Generalized Algorithmic Information - Speed Prior - The New AI