Program Synthesis by Learning and Planning
edited by Kristina Schädler, Tobias Scheffer, Ute Schmid and Fritz
Technische Universität Berlin, Computer Science Department. Technical
Report Nr. 95-20
The work reported is the outcome of a students project,
which was conducted from February to July 1995 in the Dept. of Artificial
Intelligence at the Technische Universität of Berlin. All students who
participated in the project have provided chapters for this report.
- U. Schmid and F. Wysotzki. Program Synthesis by
Learning and Planning
- S. Böhm, S. Dobratz, I. Szabo and U. Schmid. Inductive Synthesis
of Recursive Programs
- B. Parandian, U. Schmid and F. Wysotzki. Program Synthesis with a Generalized Planning Approach
- E. Heymann, D. Matzke, R. Mercy, M. Müller and K. Schädler. Functional
Programming by Analogy
- L. Briesemeister, B. van Schewick and T. Scheffer.
Combination of Problem Solving and Learning from Experience
- H. Kampe, K. Neuenhofen, A. Rother, M. Stauch and T. Scheffer. Reinforcement
Learning of Multiple Real-Valued Control Actions in a Dynamic System.