Journal of Machine Learning Research

Special Topic on Approaches and Applications of Inductive Programming

Guest Editors: Ute Schmid and Roland Olsson

We invite papers on the inductive synthesis of general programs that contain control structures such as recursion or loops for a special topic of the Journal of Machine Learning Research (JMLR). This topic is also covered in the workshop "Approaches and Applications of Inductive Programming" (AAIP) held at the 22nd International Conference on Machine Learning (ICML 2005) in Bonn, Germany, 7-11 August, 2005.

All contributors to AAIP are invited to submit a full paper, but submission is open to everyone.

Inductive synthesis of general programs is a research topic of crucial interest for machine learning and artificial intelligence in general. The ability to generalize a program containing control structures as recursion or loops from examples is a challenging problem which calls for approaches going beyond the requirements of algorithms for concept learning. Pushing research forward in this area can give important insights in the nature and complexity of learning as well as enlarging the field of possible applications.

This special topic is intended to bring together research efforts from different machine learning communities -- such as inductive logic programming, genetic programming, synthesis of functional programs, grammar inference and algorithmic learning theory -- addressing the problem of inductive program synthesis. Furthermore, applications of inductive program synthesis in different domains are of interest.

Topics of interest include:

Submission procedure:

Submit papers to the standard JMLR submission system

Please include a note stating that your submission is for the special topic on Approaches and Applications of Inductive Programming.

Important Dates:

For further details or enquiries, please contact the guest editors:

Ute Schmid (

Roland Olsson (