TY - JOUR
T1 - Learning to Predict Non-Deterministically Generated Strings
AU - Koppel, Moshe
PY - 1991/7
Y1 - 1991/7
N2 - In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.
AB - In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.
KW - Kolmogorov complexity
KW - Prediction
KW - learning in the limit
KW - minimum description length
UR - http://www.scopus.com/inward/record.url?scp=34249920705&partnerID=8YFLogxK
U2 - 10.1023/A:1022671126433
DO - 10.1023/A:1022671126433
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AN - SCOPUS:34249920705
SN - 0885-6125
VL - 7
SP - 85
EP - 99
JO - Machine Learning
JF - Machine Learning
IS - 1
ER -