Algorithmic Learning Theory: 9th International Conference, - download pdf or read online

By Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann

ISBN-10: 3540497307

ISBN-13: 9783540497301

ISBN-10: 354065013X

ISBN-13: 9783540650133

This quantity comprises all of the papers awarded on the 9th overseas Con- rence on Algorithmic studying concept (ALT’98), held on the eu schooling centre Europ¨aisches Bildungszentrum (ebz) Otzenhausen, Germany, October eight{ 10, 1998. The convention was once subsidized via the japanese Society for Arti cial Intelligence (JSAI) and the college of Kaiserslautern. Thirty-four papers on all points of algorithmic studying concept and comparable components have been submitted, all electronically. Twenty-six papers have been approved by means of this system committee according to originality, caliber, and relevance to the idea of computer studying. also, 3 invited talks provided by way of Akira Maruoka of Tohoku collage, Arun Sharma of the collage of latest South Wales, and Stefan Wrobel from GMD, respectively, have been featured on the convention. we wish to specific our honest gratitude to our invited audio system for sharing with us their insights on new and interesting advancements of their parts of study. This convention is the 9th in a chain of annual conferences verified in 1990. The ALT sequence makes a speciality of all parts relating to algorithmic studying thought together with (but no longer restricted to): the idea of laptop studying, the layout and research of studying algorithms, computational common sense of/for desktop discovery, inductive inference of recursive features and recursively enumerable languages, studying through queries, studying by means of arti cial and organic neural networks, trend acceptance, studying through analogy, statistical studying, Bayesian/MDL estimation, inductive common sense programming, robotics, program of studying to databases, and gene analyses.

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Extra info for Algorithmic Learning Theory: 9th International Conference, ALT’98 Otzenhausen, Germany, October 8–10, 1998 Proceedings

Example text

All other trees Uei will be finite. This implies that for i > 0 every tree Uei contains an infinite branch iff ϕi is an infinite branch of Te . This idea is the key to achieve C ∈ SelectMa, since the branch f of such an infinite tree Uei with i > 0 fulfills f (1) = i, that is, f (1) is a program for an infinite branch of Te . Therefore, these branches can be used as selected masters. Construction of Te = {σsi : i, s ∈ ω}: Stage 0 : For all i ∈ ω: σ0i = τ0i = ei, xi0 = 2. Stage s+1 : Learning to Win Process-Control Games 39 1.

Accompanying software available. [RLD93] L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple predicate learning. In Proceedings of the 13th International Joint Conference on Arti cial Intelligence. Morgan Kaufmann, 1993. A. Robinson. A machine-oriented logic based on the resolution principle. JACM, 12(1):23{41, January 1965. 30 [RP89] S. Wrobel Celine Rouveirol and Jean Francois Puget. Beyond inversion of resolution. In Proc. Sixth Intern. Workshop on Machine Learning, pages 122 { 130, San Mateo, CA, 1989.

Abstract. The present paper focuses on some interesting classes of process-control games, where winning essentially means successfully controlling the process. A master for one of these games is an agent who plays a winning-strategy. In this paper we investigate situations, in which even a complete model (given by a program) of a particular game does not provide enough information to synthesize — even in the limit — a winning strategy. However, if in addition to getting a program, a machine may also watch masters play winning strategies, then the machine is able to learn in the limit a winning strategy for the given game.

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Algorithmic Learning Theory: 9th International Conference, ALT’98 Otzenhausen, Germany, October 8–10, 1998 Proceedings by Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann

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