期刊
ARTIFICIAL INTELLIGENCE REVIEW
卷 29, 期 1, 页码 45-62出版社
SPRINGER
DOI: 10.1007/s10462-009-9108-7
关键词
Inductive programming; Machine learning
The research field of inductive programming is concerned with the design of algorithms for learning computer programs with complex flow of control (typically recursive calls) from incomplete specifications such as examples. We introduce a basic algorithmic approach for inductive programming and illustrate it with three systems: dialogs learns logic programs by combining inductive and abductive reasoning; the classical thesys system and its extension igor1 learn functional programs based on a recurrence detection mechanism in traces; igor2 learns functional programs over algebraic data-types making use of constructor-term rewriting systems. Furthermore, we give a short history of inductive programming, discuss related approaches, and give hints about current applications and possible future directions of research.
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