Identification in the limit, originally due to Gold [10], is a widely used computation model for inductive inference and human language acquisition. We consider a nonconstructive ...
In learning, a semantic or behavioral U-shape occurs when a learner rst learns, then unlearns, and, nally, relearns, some target concept (on the way to success). Within the framew...
In the inductive inference framework of learning in the limit, a variation of the bounded example memory (Bem) language learning model is considered. Intuitively, the new model co...
Sanjay Jain, Steffen Lange, Samuel E. Moelius, San...
Higman essentially showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. Let s1, s2, s3, . . . be the sta...
Stephen A. Fenner, William I. Gasarch, Brian Posto...
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
In this paper we survey some results in inductive inference showing how learnability of a class of languages may depend on hypothesis space chosen. We also discuss results which co...
The present work is dedicated to the study of modes of data-presentation in the range between text and informant within the framework of inductive inference. In this study, the le...