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K. Droste, E. Bollschweiler, Thomas Waschulzik, R. Engelbrecht, K.\ Maruyama, and J.R. Siewert. Preoperative prediction of lymph node metastasis in gastric cancer with neural networks. Journal of Cancer Research and Clinical Oncology, Supplement to Volume 120, 21st National Cancer Congress of the German Cancer Society, Abstracts of Lectures and Posters, 1994.

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Martin Eldracher, Alexander Staller, and René Pompl. Function approximation with continuous valued activation functions in cmac. Forschungsberichte Künstliche Intelligenz FKI-199-94, Institut für Informatik, Technische Universität München, December 1994.

Martin Eldracher and Thomas Waschulzik. A topologically distributed encoding to facilitate learning. Journal of Systems Engineering, 3:110-119, 1993.

M. Förster, K. Kirchner, Thomas Waschulzik, et al. DIADOQ: Untersuchungen zum Aufbau von Wissensbasen in der Diabetologie mittels Neuronaler Netze. In Proc. of 9. Jahrestagung der GMDS, Dresden, 1994, 1994.

M. Förster, W. Moser, Thomas Waschulzik, K. Kirchner, G. Entenmann, and T. Koschinsky. DIADOQ: Vergleich der Methoden Neuronale Netze und Kausal-Probabilistische Netze zur Realisierung von Wissensbasen in der Diabetologie am Beispiel der Diagnose des Sekundärversagens. In Abstracts zur 40. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie gmds e.V.\ Ruhr-Universität Bochum, 1995. Proceedings are to appear presumably.

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Christian Freksa. Qualitative spatial reasoning. In D. M. Mark and A. U. Frank, editors, Cognitive and Linguistic Aspects of Geographic Space, NATO Advanced Studies Institute, pages 361-372. Kluwer, 1991.

Christian Freksa. Temporal reasoning based on semi-intervals. Forschungsberichte Künstliche Intelligenz FKI-153-91, Institut für Informatik, Technische Universität München, 1991.

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Christian Freksa. Temporal reasoning based on semi-intervals. Artificial Intelligence, 54:199-227, 1992.

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D. Hernández, M. Kinder, K. Zimmermann, and W. Brauer. Standardannahmen bei der qualitativen Repr"asentation r"aumlichen Wissens. Forschungsberichte Künstliche Intelligenz FKI-165-92, Institut für Informatik, Technische Universität München, March 1992.

Daniel Hernández. Relative representation of spatial knowledge: The 2-D case. In D. M. Mark and A. U. Frank, editors, Cognitive and Linguistic Aspects of Geographic Space, NATO Advanced Studies Institute, pages 373-385. Kluwer, 1991.

Daniel Hernández. Diagrammatical aspects of qualitative representations of space. Forschungsberichte Künstliche Intelligenz FKI-164-92, Institut für Informatik, Technische Universität München, March 1992. Also in Proceedings of the 1992 AAAI Spring Symposium on Reasoning with Diagrammatic Representations, March 25-27th, 1992, pp. 225-228, Stanford University.

Daniel Hernández. Qualitative Representation of Spatial Knowledge. PhD thesis, Institut für Informatik, Technische Universität München, Prof. Dr. W. Brauer, 1992.

Daniel Hernández. Hybride und integrierte Ans"atze zur Raumrepr"asentation und ihre Anwendung. In O. Herzog, Th. Christaller, and D. Schütt, editors, Grundlagen und Anwendungen der K"unstlichen Intelligenz. 17. Fachtagung f"ur K"unstliche Intelligenz, Humboldt-Universit"at zu Berlin, Informatik Aktuell, pages 210-216, September 1993. Springer, Berlin.

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Daniel Hernández. Reasoning with qualitative representations: Exploiting the structure of space. In N. Piera Carreté and M. G. Singh, editors, Proceedings of the III IMACS International Workshop on Qualitative Reasoning and Decision Technologies--QUARDET'93--, Barcelona, pages 493-502, June 1993. CIMNE, Barcelona.

Daniel Hernández. HCI aspects of a framework for the qualitative representation of space. Forschungsberichte Künstliche Intelligenz FKI-193-94, Institut für Informatik, Technische Universität München, June 1994.

Daniel Hernández. Qualitative Representation of Spatial Knowledge, volume 804 of Lecture Notes in Artificial Intelligence. Springer, Berlin, 1994.

Daniel Hernández. HCI aspects of a framework for the qualitative representation of space. In Timothy L. Nyerges, David M. Mark, Robert Laurini, and Max J. Egenhofer, editors, Cognitive Aspects of Human-Computer Interaction for Geographic Information Systems, pages 45-59. Kluwer, Dordrecht, 1995. Proceedings of the NATO Advanced Research Workshop in Palma de Mallorca, Spain, March, 1994.

Daniel Hernández, Eliseo Clementini, and Paolino Di Felice. Qualitative distances. In Andrew U. Frank and Werner Kuhn, editors, Spatial Information Theory. A Theoretical Basis for GIS. International Conference, COSIT'95, pages 45-57. Springer, Berlin, 1995.

Daniel Hernández and Amitabha Mukerjee. Representation of spatial knowledge. Forschungsberichte Künstliche Intelligenz FKI-209-95, Institut für Informatik, Technische Universität München, 1995.

Daniel Hernández and Kai Zimmermann. Default reasoning and the qualitative representation of spatial knowledge. Forschungsberichte Künstliche Intelligenz FKI-175-93, Institut für Informatik, Technische Universität München, April 1993.

Sepp Hochreiter and J.H. Schmidhuber. Flat minimum search finds simple nets. Forschungsberichte Künstliche Intelligenz FKI-200-94, Technische Universität München, 1994.

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Sepp Hochreiter and J.H. Schmidhuber. How to bridge long time lags. Neural Computation, submitted, August 1995.

Sepp Hochreiter and J.H. Schmidhuber. Long short term memory. Forschungsberichte Künstliche Intelligenz FKI-207-94, Technische Universität München, 1995.

Stefan Högg and Irmgard Schwarzer. Composition of spatial relations. Forschungsberichte Künstliche Intelligenz FKI-163-91, Institut für Informatik, Technische Universität München, December 1991.

M. Höhfeld, Jürgen Hollatz, Stefan Miesbach, D. Obradovic, Bernd Schürmann, V. Sterzing, and Volker Tresp. Advanced neural control for industrial applications. Siemens-Bericht ZFE ST SN4 - 1/92/Höh, Siemens AG, München, 1992.

Jürgen Hollatz. Rules and precedents in legal reasoning. In Proceedings of Colloq. 'Der Computer vor dem Unbestimmten - Fuzzy Logic und neuronale Netze', 1992.

Jürgen Hollatz. Supplementing neural network learning with rule-based knowledge. In Proceedings of IJCNN 92, Beijing, volume III, pages 595-600, 1992.

Jürgen Hollatz. Integration von regelbasiertem Wissen in neuronale Netze. PhD thesis, Technische Universität München, Prof. Dr.\ Brauer, 1993.

Jürgen Hollatz. Rule-based knowledge in neural computing. In Proceedings of Grammatical Inference Workshop, University of Essex, Colchester, 1993.

Jürgen Hollatz. Lernen von Fuzzy-Regeln mit datengenerierten Entscheidungsbäumen. In GI-Workshop: Fuzzy '94, 1994.

Jürgen Hollatz, H. Behrens, D. Gawronska, and Bernd Schürmann. Recurrent and feedforward backpropagation performance studies. In Proceedings of the International Conference on Artificial Neural Networks (ICANN 91), Espoo, Finland, 24-28 June 1991, 1991.

Jürgen Hollatz and Bernd Schürmann. The ''detailed balance'' net: A stable assymmetric artificial neural system for unsupervised learning. In Proceedings of the International Conference on Neural Networks (IEEE 90), San Diego 1990, pages 453-359, 1991.

Jürgen Hollatz and Volker Tresp. Rule-based knowledge in neural computing by structuring the network architecture. In Proceedings of DAGM '92, Dresden, Germany, pages 88-95. Springer, 1992.

Jürgen Hollatz and Volker Tresp. A rule-based network architecture. In Proceedings of the International Conference on Artificial Neural Networks (ICANN 92), Brighton, pages 757-761, 1992.

Jürgen Hollatz and Volker Tresp. Structuring networks using uncertain rule-based knowledge. In Proceedings of the Conference: Neural Networks for Computing, Snowbird, Utah, 1992.

Jürgen Hollatz, Volker Tresp, and S. Ahmad. Network structuring and training using rule-based knowledge. To be published in Advances in Neural Information Processing Systems 5, 1993.

Margit Kinder. Ellipsoidal Maps: A Free Space Representation for Path Planning. In Proceedings of the Helsinki Neural Network Group Workshop 1994, HELNET94, Capri, Italy. Dynamical Systems Research Ltd, London, May 1994.

Margit Kinder. Pfadplanung in höherdimensionalen Räumen mittels generalisierender Pfadspeicherung in Ellipsoid-Karten. PhD thesis, Technische Universität München, Prof. Dr.\ Brauer, 1995.

Margit Kinder and Wilfried Brauer. Classification of trajectories - extracting invariants with a neural network. Neural Networks, 6(7):1011-1017, 1993.

Margit Kinder and Till Brychcy. A neural trajectory storage. Forschungsberichte Künstliche Intelligenz FKI-182-93, Institut für Informatik, Technische Universität München, January 1993.

Margit Kinder and Till Brychcy. Theoretical issues concerning the representation of continuous-valued input and output data in neural networks. Forschungsberichte Künstliche Intelligenz FKI-183-93, Institut für Informatik, Technische Universität München, July 1993.

Margit Kinder and Till Brychcy. Path planning for six-joint manipulators by generalization from example paths. Forschungsberichte Künstliche Intelligenz FKI-192-94, Institut für Informatik, Technische Universität München, April 1994.

Margit Kinder, Till Brychcy, and Wilfried Brauer. Neuronale Planung von Roboterbewegungen. Handout Industriemesse Systems-93, October 1993.

Margit Kinder, Angie Bücherl, and Hans Geiger. Reversible Übertragung von regelbasierten Systemen in adaptive Form durch Implementierung als neuronale Netze, 1994. German Conference on Artificial Intelligence, KI-94; Workshop Integration Neuronaler und Wissensbasierter Ansätze.

Margit Kinder and Johann Heindl. Auch ein Roboter muß lernen. Sonderreihe Forschung für Bayern, Fakultät für Mathematik, Fakultät für Informatik, Technische Unitversität München, 1(6):42-43, 1993.

Margit Kinder and Ulf Pietruschka. Verallgemeinerte Radiale Basisfunktionen zur Approximation höherdimensionaler Funktionen. In Gesellschaft für Informatik e.V., Fachausschuß 1.2 "`Inferenzsysteme"', editor, Fuzzy-Neuro-Systeme '95. Theorie und Anwendungen. Tagungsband zum 3. Workshop. 15. bis 17. November 1995. Darmstadt, pages 181-188. Published by TH Darmstadt, Sekretariat am Institut für Regelungstechnik, Technische Hochschule Darmstadt, November 1995.

Daniel Kobler. Die Generierung einer stabilen Raumdarstellung. Forschungsberichte Künstliche Intelligenz FKI-161-91, Institut für Informatik, Technische Universität München, November 1991.

E. Körner, Hans Nücke, Dagmar Böller, Dieter Butz, and H.\ Walter. Scharfsinn - Neuro-Fuzzy-Systeme lösen Klassifikations- und Steueraufgaben. Elektronik-Praxis, Vogel-Verlag, Würzburg, 3:48-56, 1992.

Ulrike Kraut, Alfred Nischwitz, and Thomas Waschulzik. Temporal resolution: A critical parameter in simulations of pulscoupled neural networks. In Proceedings of 1993 International Joint Conference on Neural Networks, volume 2, pages 1116-1119. Nagoya, 1993.

Thomas Laußermair. Hyperflächen-Annealing. PhD thesis, Technische Universität München, Prof. Dr.\ Brauer, April 1992.

Thomas Laußermair and Gerhard Weiß. Artificial Life: Eine Einführung. Forschungsberichte Künstliche Intelligenz FKI-152-91, Institut für Informatik, Technische Universität München, June 1991.

Thomas Martinetz and Jürgen Hollatz. Neuro-Fuzzy in der Prozeßautomatisierung. expert-Verlag, Renningen, 1995.

Ralph Neuneier, F. Hergert, F. Finnoff, and Dirk Ormoneit. Estimation of conditional densities: A comparison of neural network approaches. In Proceedings of the International Conference on Artificial Neural Networks (ICANN), Sorrento / Italy, volume 1, pages 689-692, 1994.

Ralph Neuneier and Dirk Ormoneit. Reliable neural network predictions in the presence of outliers and non-constant variances. In Proceedings of the Neural Networks in the Capital Markets (NNCM), London/England, 1995.

Martina Nöhmeier, Thomas Waschulzik, Wilfried Brauer, Franziska Grothe, and R. Engelbrecht. A rule-based system for realisation of medical projects with neural networks (HEAD). In Proceedings of the International Conference on Neural Networks and Expert Systems in Medicine and Healthcare, University of Plymouth, Plymouth, 1994.

Martina Nöhmeier, Thomas Waschulzik, M. Förster, Franziska Grothe, Wilfried Brauer, T. Schütz, and R. Engelbrecht. Erstellung und Evaluierung eines wissensbasierten Systems für die Durchführung von Projekten mit Neuronalen Netzen in der Medizin (HEAD). In H. Kunath, editor, Medizin und Informatik, Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Beiometrie und Epidemiologie (GMDS). MVV Medizin-Verlag München, 1995.

Dirk Ormoneit and Volker Tresp. Improved gaussian mixture density estimates using bayesian penalty terms and network averaging. In Neural Information Processing Systems (NIPS), Denver / USA, 1995. accepted.

Ulf Pietruschka and Margit Kinder. Ellipsoidal basis functions for higher-dimensional approximation problems. In F. Fogelman-Soulié and P. Gallinari, editors, ICANN '95 International Conference on Artificial Neural Networks, Neuron^ımes '95, Scientific Conference (ICANN-95)., pages 81-86. EC2 & Cie, Paris, Paris, France, October 1995.

Kerstin Quandt, Thomas Waschulzik, M. Lewis, A. Hörmann, R.\ Engelbrecht, and Wilfried Brauer. Evaluation of epidemiological data with neural networks. In World Congress on Neural Networks, volume 1, pages 1257-1260. Lawrence Erlbaum Assiciates, Inc., Publishers, Hillsdale, New Jersay, 1993.

Gerda Ruge and Wilfried Brauer. Warum Heads und Modifiers bei der Korpusanalyse. LDV-Forum, accepted, 1995.

Bernhard Schätz. Portierung eines neuronalen Netzwerksimulators auf ein Transputersystem. In R. Grebe et al., editors, Abstract collection of the 2.\ bundesweiten Transputer-Anwender-Treffens TAT'90, RWTH Aachen, 17./18. 09 1990, number 272 in Lecture Note in Computer Science, pages 48-49. Springer, Berlin, September 1990.

Gabriele Scheler. The use of an adaptive distance measure in generalizing pattern learning. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, volume 1, pages 131-135. North Holland, 1992.

Gabriele Scheler. 36 problems for semantic interpretation. Forschungsberichte Künstliche Intelligenz FKI-179-93, Institut für Informatik, Technische Universität München, 1993.

Gabriele Scheler. Feature selection with exception handling using adaptive distance measures. Forschungsberichte Künstliche Intelligenz FKI-178-93, Institut für Informatik, Technische Universität München, July 1993.

Gabriele Scheler. Extracting semantic features for aspectual meanings from a syntactic representation using neural networks. In Proc. NeMLaP 94 (Int. Conf. on New Methods in Language Processing), Manchester, UK, pages 198-204, 1994.

Gabriele Scheler. Extracting semantic features for aspectual meanings from a syntactic representation using neural networks. Forschungsberichte Künstliche Intelligenz FKI-191-94, Institut für Informatik, Technische Universität München, 1994.

Gabriele Scheler. Feature selection with exception handling-- an example from phonology. In Robert Trappl, editor, Proceedings of the European Meeting on Systems and Cybernetics, 1994.

Gabriele Scheler. Machine translation of aspectual categories using neural networks. In Proceedings of the Workshop ``Integration Neuronaler und Wissensbasierter Ansätze'', Saarbrücken, 1994.

Gabriele Scheler. Modelling aspectual semantics with neural networks. In 1. Fachtagung der Gesellschaft für Kognitionswissenschaft, (poster presentation), 1994.

Gabriele Scheler. Multilingual generation of grammatical categories. Forschungsberichte Künstliche Intelligenz FKI-190-94, Institut für Informatik, Technische Universität München, April 1994.

Gabriele Scheler. Pattern classification with adaptive distance measures. Forschungsberichte Künstliche Intelligenz FKI-188-94, Institut für Informatik, Technische Universität München, January 1994.

Gabriele Scheler. Phoneme learning as a feature selection process. In World Congress on Neural Networks WCNN-94, San Diego, 1994. Lawrence Erlbaum Associates, Inc., Publishers, Hillsdale, 1994.

Gabriele Scheler. Learning the semantics of aspect. In D. Jones, editor, New Methods in Language Processing. University College London Press, 1995.

Gabriele Scheler. Neuronale Lernverfahren zur Modellierung der Semantik spatialer Ausdrücke - Stand der Forschung und Entwicklung neuerer Forschungsansätze. Forschungsberichte Künstliche Intelligenz FKI-204-95, Institut für Informatik, Technische Universität München, April 1995.

Gabriele Scheler and Johann Schumann. A hybrid model of semantic inference. In Alex Monaghan, editor, Proceedings of the 4th International Conference on Cognitive Science in Natural Language Processing (CSNLP 95), pages 183-193, 1995.

Christian Schittenkopf, Gustavo Deco, and Wilfried Brauer. Using principal component analysis to avoid overfitting in feed forward-networks. Technical report, Siemens AG, Technische Universität, München, 1994. submitted to Neural Networks.

Christian Schittenkopf, Gustavo Deco, and Wilfried Brauer. A novel pruning method to avoid overfitting in feed-forward networks. In F. Fogelman-Soulié and P. Gallinari, editors, ICANN '95 International Conference on Artificial Neural Networks, Neuron^ımes '95, Scientific Conference (ICANN-95)., volume 2, pages 437-442. EC2 & Cie, Paris, October 1995.

Christian Schittenkopf, Gustavo Deco, and Wilfried Brauer. Two strategies to avoid overfitting in feed-forward networks. Neural Networks, to appear, 1996.

J.H. Schmidhuber. Adaptive curiosity and adaptive confidence. Forschungsberichte Künstliche Intelligenz FKI-149-91, Institut für Informatik, Technische Universität München, April 1991.

J.H. Schmidhuber. Adaptive decomposition of time. In T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas, editors, Artificial Neural Networks. Proceedings of the 1991 International Conference on Artificial Neural Networks (ICANN-91) Espoo, Finland, pages 909-914. Amsterdam: Elsevier Publishers B.V., North-Holland, June 1991.

J.H. Schmidhuber. Adaptive history compression for learning to divide and conquer. In Proceedings of the International Joint Conference on Neural Networks, Singapore, volume 2, pages 1130-1135. IEEE, 1991.

J.H. Schmidhuber. Curious model-building control systems. In Proceedings of the International Joint Conference on Neural Networks, Singapore, volume 2, pages 1458-1463. IEEE, 1991.

J.H. Schmidhuber. Learning to generate sub-goals for action sequences. In T. Kohonen et al., editors, Artificial Neural Networks, pages 967-972. Amsterdam: Elsevier Publishers B.V., North-Holland, 1991.

J.H. Schmidhuber. Learning to generate subgoals for action sequences. In T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas, editors, Artificial Neural Networks. Proceedings of the 1991 International Conference on Artificial Neural Networks (ICANN-91) Espoo, Finland. Amsterdam: Elsevier Publishers B.V., North-Holland, June 1991.

J.H. Schmidhuber. Neural sequence chunkers. Forschungsberichte Künstliche Intelligenz FKI-148-91, Institut für Informatik, Technische Universität München, April 1991.

J.H. Schmidhuber. An o( tex2html_wrap_inline1042 ) learning algorithm for fully recurrent networks. Forschungsberichte Künstliche Intelligenz FKI-151-91, Institut für Informatik, Technische Universität München, May 1991.

J.H. Schmidhuber. A possibility for implementing curiosity and boredom in model-building neural controllers. In Jean-Arcady Meyer and S.W. Wilson, editors, Proc. of the International Conference on Simulation of Adaptive Behavior: From Animals to Animats, Paris 1990, pages 222-227. MIT Press/Bradford Books, 1991.

J.H. Schmidhuber. Reinforcement learning in Markovian and non-Markovian environments. In D.S. Lippmann et al., editors, Advances in Neural Information Processing Systems 3, pages 500-506. San Mateo, CA: Morgan Kaufmann, 1991.

J.H. Schmidhuber. A fixed size o( tex2html_wrap_inline1042 ) time complexity learning algorithm for fully recurrent continually running networks. Neural Computation, 4(2):234-242, 1992.

J.H. Schmidhuber. Learning complex extended sequences using the principle of history compression. Neural Computation, 4(1):131-139, 1992.

J.H. Schmidhuber. Learning factorial codes by predictability minimization. Neural Computation, 4(6):873-879, 1992.

J.H. Schmidhuber. Learning unambiguous reduced sequence descriptions. In J.E. Moody, S.J. Hanson, and R.P. Lippman, editors, Advances in Neural Information Processing Systems 4, pages 291-298. San Mateo, CA: Morgan Kaufmann, 1992.

J.H. Schmidhuber. An introspective network that can learn to run its own weight change algorithm. In Proc. of the Int. Conf. on Artificial Neural Networks, Brighton, pages 191-195. IEEE, 1993.

J.H. Schmidhuber. Netzwerkarchitekturen, Zielfunktionen und Kettenregel. Habilitationsschrift, Institut für Informatik, Technische Universität München, 1993.

J.H. Schmidhuber. A neural network that embeds its own meta-levels. In Proceedings of the International Conference on Neural Networks '93, San Francisco, IEEE, 1993.

J.H. Schmidhuber. ``Neural'' redundancy reduction for text compression. Neural Network World, 3(6):849-853, 1993.

J.H. Schmidhuber. On decreasing the ratio between learning complexity and number of time-varying variables in fully recurrent nets. In Proceedings of the International Conference on Artificial Neural Networks, Amsterdam, pages 460-463. Springer, 1993.

J.H. Schmidhuber. A self-referential weight matrix. In Proceedings of the International Conference on Artificial Neural Networks, Amsterdam, pages 446-451. Springer, 1993.

J.H. Schmidhuber. Algorithmic art. Forschungsberichte Künstliche Intelligenz FKI-197-94, Institut für Informatik, Technische Universität München, 1994.

J.H. Schmidhuber. Discovering problem solutions with low Kolmogorov complexity and high generalization capability. Forschungsberichte Künstliche Intelligenz FKI-194-94, Institut für Informatik, Technische Universität München, 1994.

J.H. Schmidhuber. Neural predictors for detecting and removing redundant information. In H. Cruse, J. Dean, and H. Ritter, editors, Adaptive Behavior and Learning, number 9 in ZiF Preprint Series, pages 135-145. ZiF, Center for Interdisciplinary Research, Universität Bielefeld, 1994.

J.H. Schmidhuber. Beyond ``genetic programming'': Incremental self-improvement. In Justinian Rosca, editor, Proc. Workshop on Genetic Programming at ML95, pages 42-49. National Resource Lab for the study of Brain and Behavior, 1995.

J.H. Schmidhuber. Environment-independent reinforcement acceleration. Technical Report Note IDSIA-59-95, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), June 1995. Invited talk at Hongkong University of Science and Technology.

J.H. Schmidhuber, M. Eldracher, and B. Foltin. Semilinear predictability minimization produces orientation sensitive edge detectors. Neural Computation, Conditionally Accepted, 1995.

J.H. Schmidhuber and B. Foltin. Semilinear predictability minimization produces orientation sensitive edge detectors. Forschungsberichte Künstliche Intelligenz FKI-201-94, Technische Universität München, December 1994.

J.H. Schmidhuber and S. Heil. Predictive coding with neural nets: Application to text compression. In G. Tesauro, D.S. Touretzky, and T.K. Leen, editors, Advances in Neural Information Processing Systems 7. MIT Press, Cambridge MA, 1994. Presented at NIPS 94.

J.H. Schmidhuber and R. Huber. Using adaptive sequential neurocontrol for efficient learning of translation and rotation invariance. In T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas, editors, Artificial Neural Networks. Proceedings of the 1991 International Conference on Artificial Neural Networks (ICANN-91) Espoo, Finland, pages 315-320. Amsterdam: Elsevier Publishers B.V., North-Holland, June 1991.

J.H. Schmidhuber and Rudolf Huber. Learning to generate artificial fovea trajectories for target detection. International Journal of Neural Systems, 2(1&2):135-141, 1991.

J.H. Schmidhuber, M.C. Mozer, and Daniel Prelinger. Continuous history compression. In H. Hüning, S. Neuhauser, M. Raus, and W. Ritschel, editors, Proceedings of International Workshop on Neural Networks , RWTH Aachen, Augustinus, pages 87-95, 1993.

J.H. Schmidhuber and Daniel Prelinger. Discovering predictable classifications. Neural Computation, 5(4):625-635, 1993.

J.H. Schmidhuber and Daniel Prelinger. A novel unsupervised classification method. In Proceedings of the International Conference on Artificial Neural Networks, Brighton, IEEE, pages 91-96, 1993.

J.H. Schmidhuber and Daniel Prelinger. Unsupervised extraction of predictable abstract features. In S. Gielen and B. Kappen, editors, Proceedings of the International Conference on Artificial Neural Networks, ICANN `93, Amsterdam, pages 601-604. Springer, 1993.

J.H. Schmidhuber and R. Wahnsiedler. Planning simple trajectories using neural subgoal generators. In J.Ã. Meyer, H. Roitblat, and S. Wilson, editors, Proc.\ of the 2nd International Conference on Simulation of Adaptive Behavior, pages 196-202. MIT Press, 1992.

Bernd Schürmann, D. Gawronska, and Jürgen Hollatz. Learning properties of multi-layer perceptrons with and without feedback. In CLNL Workshop, Berkley, Sept. 1991, Tagungsband. The MIT Press, Cambridge, Massachusetts, 1992.

Bernd Schürmann, G. Hirzinger, Daniel Hernández, H.Ũ. Simon, and H. Hackbarth. Neural control within the BMFT-project NERES. In Wilfried Brauer and Daniel Hernández, editors, Verteilte Künstliche Intelligenz und kooperatives Arbeiten. Proceedings of the 4.\ International GI-Kongreß Wissensbasierte Systeme, München, number 291 in Informatik Fachberichte, pages 533-544. Springer, Berlin, October 1991.

H. Stöcker. Taschenbuch mathematischer Formeln und moderner Verfahren. Harri Deutsch Verlag, Frankfurt/Main, 1992. Ko-Autor Jürgen Hollatz.

Jan Storck, Sepp Hochreiter, and Jürgen Schmidhuber. Reinforcement driven information acquisition in non-deterministic environments. In Proceedings of the International Conference on Artificial Neural Networks, Paris, volume 2, pages 159-164. EC2 & Cie, Paris, 1995.

Michael Sturm, Klaus Eder, Wilfried Brauer, and J.C. González. Hybridization of Neural and Fuzzy Systems by a Mutli Agent Architecture for Motor Gearbox Control. In Gesellschaft für Informatik e.V., Fachausschuß 1.2 "`Inferenzsysteme"', editor, Fuzzy-Neuro-Systeme '95. Theorie und Anwendungen. Tagungsband zum 3. Workshop. 15. bis 17. November 1995. Darmstadt. Published by TH Darmstadt, Sekretariat am Institut für Regelungstechnik, 1995.

P. Turck and G. Weiß. Eine Experimentierumgebung für verteiltes Lernen und Scheduling. Forschungsberichte Künstliche Intelligenz FKI-202-94, Institut für Informatik, Technische Universität München, 1994.

I. Wachsmuth, C.-R. Rollinger, and W. Brauer. KI-95: Advances in Artificial Intelligence. In Proc. of the 19th Annual German Conference on AI, Bielefeld, September 1995, volume 981 of Lecture Notes in Artificial Intelligence, LNCS. Berlin: Springer, 1995.

Thomas Waschulzik. Neuronale Netze in der medizinischen Bildanalyse - Anwendungen und Aspekte der Qualitätssicherung und Qualitätskontrolle. In Leonie Dreschler-Fischer and Simone Pribbenow, editors, KI-95 Activities: Workshops, Posters, Demos - Extended Abstracts, 19th Annual German Conference on Artificial Intelligence, KI-95, Bielefeld, September 11-13, 1995.

Thomas Waschulzik, Wilfried Brauer, M. Förster, K. Kirchner, R.\ Engelbrecht, T. Schütz, T. Koschinsky, and G. Entenmann. Quality assurance and increased efficiency in medical projects with neural networks by using a structured development method for feedforward neural networks. In P. Barahona et al., editors, 5th Conference on Artificial Intelligence in Medicine Europe, AIME '95, Pavia, Italy, number 934 in Lecture Notes in Computer Science, pages 343-354. Springer, 1995.

Thomas Waschulzik, Dieter Butz, Dagmar Böller, Hans Geiger, and H.\ Walter. Neuronale Netze in der Automatisierungstechnik. In Wilfried Brauer and Daniel Hernández, editors, Verteilte künstliche Intelligenz und kooperatives Arbeiten. 4. Internationaler GI Kongreß "`Wissensbasierte Systeme"', volume 291 of Informatik-Fachberichte, Oct. 1991, pages 486-497. Springer, Berlin, 1991.

Thomas Waschulzik, Kerstin Quandt, M. Lewis, A. Hörmann, R.\ Engelbrecht, and Wilfried Brauer. Evaluation of an epidemiological data set as an example of the application of neural networks to the analysis of large medical data sets. In Artificial Intelligence in Medicine, Proceedings of the 4th Conference on Artificial Intelligence in Medicine Europe, AIME`93, 3.-6.10.1993, München, Artificial Intelligence in Medicine, pages 466-476. IOS Press, Amsterdam, 1993.

Gerhard Weiß. The action-oriented bucket brigade. Forschungsberichte Künstliche Intelligenz FKI-156-91, Institut für Informatik, Technische Universität München, August 1991.

Gerhard Weiß. Action-oriented learning in classifier systems. Forschungsberichte Künstliche Intelligenz FKI-158-91, Institut für Informatik, Technische Universität München, 1991.

Gerhard Weiß. Action selection and learning in multi-agent systems. Forschungsberichte Künstliche Intelligenz FKI-170-92, Institut für Informatik, Technische Universität München, October 1992.

Gerhard Weiß. Collective learning and action coordination. Forschungsberichte Künstliche Intelligenz FKI-166-92, Institut für Informatik, Technische Universität München, April 1992.

Gerhard Weiß. Learning the goal relevance of actions in classifier systems. In B. Neumann, editor, Proceedings of the 10th European Conference on Artificial Intelligence, Wien, Aug. 3-7, pages 430-434. Chechester: Wiley, S., 1992.

Gerhard Weiß. Towards the synthesis of neural and evolutionary learning. Interner bericht, Institut für Informatik, Technische Universität München, 1992. In O. Omidvar & C. Wilson (Eds.), Progress in Neural Networks (Vol. 5, Chapter 5). Norwood, New Jersey: Ablex Publ. Corp.

Gerhard Weiß. Action selection and learning in multi-agent environments. In S.W. Wilson et al., editors, From animals to animats 2 - Proceedings of the 2nd International Conference on Simulation of Adaptive Behavior, Honolulu, Dez. 7-11, 1992, pages 502-510. Cambridge: MIT Press, 1993.

Gerhard Weiß. Collective learning of action sequences. In Proceedings of the 13th International Conference on Distributed Computing Systems, Pittsburgh, Mai 25-28, 1993, pages 203-209. Los Alamitos: IEEE Computer Society Press, 1993.

Gerhard Weiß. Learning to coordinate actions in multi-agent systems. In R. Bajcsy, editor, Proceedings of the 13th International Joint Conference on Artificial Intelligence, Aug. 28 - Sept. 3, 1993, pages 311-316. San Mateo: Morgan Kaufmann, 1993.

Gerhard Weiß. Lernen und Aktionskoordinierung in Mehragentensystemen. In J. Müller, editor, Verteilte Künstliche Intelligenz - Methoden und Anwendungen, pages 112-132. Mannheim: BI Verlag, 1993.

Gerhard Weiß. Distributed machine learning. PhD thesis, Institut für Informatik, Technische Universität München, Prof. Dr. W. Brauer, 1994.

Gerhard Weiß. Hierarchical chunking in classifier systems. In Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, Wash., USA, Juli 31 - Aug. 4, pages 1335-1340. Menlo Park, CA: AAAI Press, 1994.

Gerhard Weiß. The locality/globality dilemma in classifier systems and an approach to its solution. Forschungsberichte Künstliche Intelligenz FKI-187-94, Institut für Informatik, Technische Universität München, 1994.

Gerhard Weiß. Neural networks and evolutionary computation, Part I: Hybrid approaches in Artificial Intelligence. In Proceedings of the IEEE International Conference on Evolutionary Computation, Orlando, Florida, USA, Juni 26 - Juli 2, 1994, pages 268-272. New York: IEEE Press, 1994.

Gerhard Weiß. Neural networks and evolutionary computation, Part II: Hybrid approaches in Neurosciences. In Proceedings of the IEEE International Conference on Evolutionary Computation, Orlando, Florida, USA, Juni 26 - Juli 2, 1994, pages 273-277. New York: IEEE Press, 1994.

Gerhard Weiß. Some studies in distributed machine learning and organizational design. Forschungsberichte Künstliche Intelligenz FKI-189-94, Institut für Informatik, Technische Universität München, 1994.

Gerhard Weiß. An action-oriented perspective of learning in classifier systems. To appear in Journal of Experimental and Theoretical Artificial Intelligence, 1995.

Gerhard Weiß. Adaptation and learning in multi-agent systems. To appear: Winter 1995/Spring 1996, 1995.

Gerhard Weiß. Distributed machine learning. Sankt Augustin, Germany: infix, 1995. ISBN 3-929037-75-0.

Gerhard Weiß. Distributed reinforcement learning. Robotics and Autonomous Systems, 15:135-142, 1995. Appeared also in L. Steels (Ed.), The Biology and Technology of Intelligent Autonomous Agents. NATO ASI Series, Subseries F, Vol. 144, pp. 415-428. Berlin: Springer. 1995.

Gerhard Weiß. Towards the synthesis of neural and evolutionary learning. To appear in O. Omidvar & C.L. Wilson (Eds.), Progress in Neural Networks (Vol. V, Chapter 5). Norwood, New Jersey: Ablex Publ. Corp.\ 1995., 1995.

Kai Zimmermann. SEqO: Ein System zur Erforschung qualitativer Objektrepr"asentationen. Forschungsberichte Künstliche Intelligenz FKI-154-91, Institut für Informatik, Technische Universität München, July 1991.

K.W. Zimmermann. Empirical explorations and simulations in the field of neighborhood-based reasoning. Manuscripts and program documentation. Parts of the computational results are published in: Freksa, C.(1991): Temporal Reasoning Based on Semi-Intervals. Report FKI-153-91, Technische Universität München, 1991.



Dieter Butz
Wed Nov 20 12:16:55 MET 1996