Reinforcement learning with recurrent neural networks.

Anton Maximilian Schäfer Anton Maximilian Schäfer Reinforcement learning with recurrent neural networks. 2008 University of Osnabrück, Germany 1-98 http://elib.ub.uni-osnabrueck.de/publications/diss/html/E-Diss839_HTML.html https://nbn-resolving.org/urn:nbn:de:gbv:700-2008112111 https://d-nb.info/991415167 https://d-nb.info/992727235

Anton Maximilian Schäfer Steffen Udluft Hans-Georg Zimmermann Learning long-term dependencies with recurrent neural networks. 2481-2488 2008 71 Neurocomputing 13-15 https://doi.org/10.1016/j.neucom.2007.12.036 db/journals/ijon/ijon71.html#SchaferUZ08

Alexander Hans Daniel Schneegaß Anton Maximilian Schäfer Steffen Udluft Safe exploration for reinforcement learning. 143-148 2008 ESANN https://www.esann.org/sites/default/files/proceedings/legacy/es2008-36.pdf conf/esann/2008 db/conf/esann/esann2008.html#HansSSU08

Anton Maximilian Schäfer Hans-Georg Zimmermann Recurrent Neural Networks are Universal approximators. 253-263 2007 17 Int. J. Neural Syst. 4 https://doi.org/10.1142/S0129065707001111 https://www.wikidata.org/entity/Q51908039 db/journals/ijns/ijns17.html#SchaferZ07

Anton Maximilian Schäfer Steffen Udluft Hans-Georg Zimmermann The Recurrent Control Neural Network. 319-324 2007 ESANN https://www.esann.org/sites/default/files/proceedings/legacy/es2007-54.pdf conf/esann/2007 db/conf/esann/esann2007.html#SchaferUZ07 Daniel Schneegaß Anton Maximilian Schäfer Thomas Martinetz The Intrinsic Recurrent Support Vector Machine. 325-330 2007 ESANN https://www.esann.org/sites/default/files/proceedings/legacy/es2007-3.pdf conf/esann/2007 db/conf/esann/esann2007.html#SchneegassSM07 Anton Maximilian Schäfer Daniel Schneegaß Volkmar Sterzing Steffen Udluft A Neural Reinforcement Learning Approach to Gas Turbine Control. 1691-1696 2007 IJCNN https://doi.org/10.1109/IJCNN.2007.4371212 conf/ijcnn/2007 db/conf/ijcnn/ijcnn2007.html#SchaeferSSU07 Anton Maximilian Schäfer Steffen Udluft Hans-Georg Zimmermann Learning Long Term Dependencies with Recurrent Neural Networks. 71-80 2006 conf/icann/2006-1 ICANN (1) https://doi.org/10.1007/11840817_8 db/conf/icann/icann2006-1.html#SchaferUZ06 Anton Maximilian Schäfer Hans-Georg Zimmermann Recurrent Neural Networks Are Universal Approximators. 632-640 2006 conf/icann/2006-1 ICANN (1) https://doi.org/10.1007/11840817_66 db/conf/icann/icann2006-1.html#SchaferZ06 Hans-Georg Zimmermann Lorenzo Bertolini Ralph Grothmann Anton Maximilian Schäfer Christoph Tietz A Technical Trading Indicator Based on Dynamical Consistent Neural Networks. 654-663 2006 conf/icann/2006-2 ICANN (2) https://doi.org/10.1007/11840930_68 db/conf/icann/icann2006-2.html#ZimmermannBGST06 Hans-Georg Zimmermann Ralph Grothmann Anton Maximilian Schäfer Christoph Tietz Dynamical consistent recurrent neural networks. 1537-1541 2005 IJCNN https://doi.org/10.1109/IJCNN.2005.1556106 conf/ijcnn/2005 db/conf/ijcnn/ijcnn2005.html#ZimmermannGST05 streams/conf/ijcnn Lorenzo Bertolini Ralph Grothmann Alexander Hans Thomas Martinetz Daniel Schneegaß Volkmar Sterzing Christoph Tietz Steffen Udluft Hans-Georg Zimmermann