A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is application/pdf.
Complexity Issues in Robotic Machine Learning of Natural Language
[chapter]
1992
Modeling Complex Phenomena
Preserved Fulltext
In Sections 1, 2 'and 3, the theoretical framework we have been developing for a probabilistic theory of machine learning of natural language is outlined. In Section 4, some simple examples showing how mean learning curves can be constructed from the theory are given. But we also show that the explicit computation of the mean learning curve for an arbitrary number of sentences is unfeasible. This result holds even when the learning itself is quite rapid. In Section 5 we briefly describe the
doi:10.1007/978-1-4613-9229-3_4
fatcat:hielbmq7arfm5bxtjnqdxmchoi