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ORCIDGOSLER Final Report: 1995
- Klaus P. Jantke, Steffen Lange:
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report. Lecture Notes in Computer Science 961, Springer 1995, ISBN 3-540-60217-8
1 Inductive Inference Theory
1.1 Inductive Inference of Recursive Functions
- Rolf Wiehagen, Thomas Zeugmann:
Learning and Consistency. 1-24 - Rusins Freivalds, Efim B. Kinber, Rolf Wiehagen:
Error Detecting in Inductive Inference. 25-48 - Rusins Freivalds, Efim B. Kinber, Rolf Wiehagen:
Learning from Good Examples. 49-62 - Robert P. Daley, Bala Kalyanasundaram:
Towards Reduction Argumentf for FINite Learning. 63-75 - John Case, Mandayam Suraj, Sanjay Jain:
Not-So-Nearly-Minimal-Size Program Inference. 76-95 - Andris Ambainis:
Optimization Problem in Inductive Inference. 96-107 - Sanjay Jain, Arun Sharma:
On Identification by Teams and Probabilistic Machines. 108-145 - Kalvis Apsitis:
Topological Considerations in Composing Teams of Learning Machines. 146-154 - Rusins Freivalds, Efim B. Kinber, Carl H. Smith:
Probabilistic versus Deterministic Memory Limited Learning. 155-161 - William I. Gasarch, Mark G. Pleszkoch, Mahendran Velauthapillai:
Classification Using Information. 162-173
1.2 Inductive Inference of Formal Languages
- Rolf Wiehagen, Carl H. Smith, Thomas Zeugmann:
Classifying Recursive Predicates and Languages. 174-189 - Thomas Zeugmann, Steffen Lange:
A Guided Tour Across the Boundaries of Learning Recursive Languages. 190-258 - Takeshi Shinohara, Setsuo Arikawa:
Pattern Inference. 259-291 - Phil Watson:
Inductive Learning of Recurrence-Term Languages from Positive Data. 292-315 - Yuji Takada:
Learning Formal Languages Based on Control Sets. 316-339
2 Inductive Inference for Artificial Intelligence
2.1 Theoretical Approaches
- Christoph Globig, Stefan Wess:
Learning in Case-Based Classification Algorithms. 340-362 - Christian Posthoff, Michael Schlosser:
Optimal Strategies - Learning from Examples - Boolean Equations. 363-390 - Gerhard Mehlsam, Hermann Kaindl, Wilhelm Barth:
Feature Construction during Tree Learning. 391-403 - Andreas Alexander Albrecht:
On Lower Bounds for the Depth of Threshold Circuits with Weights from {-1, 0, +1}. 404-416 - Eberhard Pippig:
Structuring Neural Networks and PAC-Learning. 417-434 - Ulf Goldammer:
Inductive Synthesis of Rewrite Programs. 435-466
2.2 Systems
- Gunter Grieser:
TLPS - a Term Rewriting Laboratory (not only) for Experiments in Automatic Program Synthesis. 467-481 - Hans-Rainer Beick, Ventsislav Stankov:
GolerP - A Logic Programming Tool for Inductive Inference. 482-510
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