A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Applied Logic Series
This paper discusses the integration of traditional abductive and inductive reasoning methods in the development of machine learning systems. In particular, the paper discusses our recent w ork in two areas: 1 The use of traditional abductive methods to propose revisions during theory re nement, where an existing knowledge base is modi ed to make it consistent with a set of empirical data; and 2 The use of inductive learning methods to automatically acquire from examples a diagnostic knowledge base used for abductive reasoning.doi:10.1007/978-94-017-0606-3_12 fatcat:avw2ihmewra5jgkljimh4ea2ue