Abstract
Philosophers have pondered the phenomenon of learning for millennia; scientists and psychologists have studied learning for more than a century. But the analysis of learning as a computational and algorithmic phenomenon is much more recent, going back only a few decades. Learning theory is now an active research area that incorporates ideas, problems, and techniques from a wide range of disciplines including statistics, artificial intelligence, information theory, pattern recognition, and theoretical computer science. Learning theory has many robust connections with more applied research in machine learning and has made significant contributions to the development of applied systems and to fields such as electronic commerce and computational biology.
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© 2007 Springer-Verlag Berlin Heidelberg
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Hutter, M., Servedio, R.A., Takimoto, E. (2007). Editors’ Introduction. In: Hutter, M., Servedio, R.A., Takimoto, E. (eds) Algorithmic Learning Theory. ALT 2007. Lecture Notes in Computer Science(), vol 4754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75225-7_1
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DOI: https://doi.org/10.1007/978-3-540-75225-7_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75224-0
Online ISBN: 978-3-540-75225-7
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