Special Issue on
Algorithmic Learning Theory
for AII'92 in the
Journal of Experimental & Theoretical
Artificial Intelligence Vol. 6, No. 1, 1994.
The Special Issue on Algorithmic Learning Theory for AII'92 in the
Journal of Experimental & Theoretical Artificial Intelligence
has been edited by
Table of Contents
- K.P. Jantke. Editorial, 1.
- J. Case. Infinitary self-reference in learning theory, 3 - 16.
- J. Case, D.S. Rajan, and A.M. Shende.
Spatial/kinematic domain and lattice computers, 17 - 40.
- R. Daley, B. Kalyanasundaram, and M. Velauthapillai.
The power of probabilism in popperian FINite learning, 41 - 62.
- R. Freivalds and A. Hoffmann. An inductive inference appraoch to
classification, 63 - 72.
- S. Lange and T. Zeugmann. Characterization of language learning
from informant under various monotonicity constraints, 73 - 94.
- N. Lavrac and S. Dzeroski. Weakening the language
bias in LINUS, 95 - 120.
- S. Muggleton. Predicate invention and utilization, 121 - 130.
- R. Wiehagen and T. Zeugmann. Ignoring data may be the only way
to learn efficiently, 131 - 144.
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