Data-Driven Detection of Recursive Program Schemes

Authors:
Martin Hofmann;Ute Schmid
Affiliations:
Faculty Information Systems and Applied Computer Science, University of Bamberg, email: {martin.hofmann, ute.schmid}@uni-bamberg.de;Faculty Information Systems and Applied Computer Science, University of Bamberg, email: {martin.hofmann, ute.schmid}@uni-bamberg.de
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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Abstract

We present an extension to a current approach to inductive programming (IGOR2), that is, learning (recursive) programs from incomplete specifications such as input/outout examples. IGOR2 uses an analytical, example-driven strategy for generalization. We extend the set of IGOR2's refinement operators by a further operator --identification of higher-order schemes --and can show that this extension does improve speed as well as scope.