Program Synthesis by Learning and Planning

edited by Kristina Schädler, Tobias Scheffer, Ute Schmid and Fritz Wysotzki

Technische Universität Berlin, Computer Science Department. Technical Report Nr. 95-20

Preface

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.

Program Synthesis by Learning and Planning

edited by Kristina Schädler, Tobias Scheffer, Ute Schmid and Fritz Wysotzki

Technische Universität Berlin, Computer Science Department. Technical Report Nr. 95-20

Preface

Contents