Integrating Abduction and Induction in Machine Learning [chapter]

Raymond J. Mooney
2000 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