Abstract
“Learning” is a complex phenomenon that is studied in different scientific disciplines. A computer program with the ability to “learn” contains mechanisms for gathering and evaluating information and, consequently, for improving its performance. Algorithmic Learning Theory provides a mathematical foundation for the study of learning programs. It is concerned with the design and analysis of learning algorithms. The analysis proceeds in a formal model such as to provide measures for the performance of a learning algorithm or for the inherent hardness of a given learning problem.
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© 2005 Springer-Verlag Berlin Heidelberg
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Jain, S., Simon, H.U., Tomita, E. (2005). Editors’ Introduction. In: Jain, S., Simon, H.U., Tomita, E. (eds) Algorithmic Learning Theory. ALT 2005. Lecture Notes in Computer Science(), vol 3734. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564089_1
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DOI: https://doi.org/10.1007/11564089_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29242-5
Online ISBN: 978-3-540-31696-1
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