Safe exploration for reinforcement learning

ESANN 2008 Proceedings, 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning

Volumn , Issue , 2008, Pages 143-148

  Hans, Alexander ^a,b   Schneegaß, Daniel ^a,c   Schäfer, Anton M ^a,d   Udluft, Steffen ^a  

^a SIEMENS AG   (Germany)

^b ILMENAU UNIVERSITY OF TECHNOLOGY   (Germany)

^c UNIVERSITY OF LÜBECK   (Germany)

^d UNIVERSITY OF OSNABRÜCK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROLLED SYSTEM; CRITICAL STATE; SAFETY CONSTRAINT; SAFETY DEGREE; SAFETY FUNCTIONS;

CRITICAL CURRENT DENSITY (SUPERCONDUCTIVITY); NEURAL NETWORKS;

REINFORCEMENT LEARNING;

EID: 79956136559     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. R.S. Sutton and A.G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.
2. A.M. Schaefer, D. Schneegass, V. Sterzing, and S. Udluft. A neural reinforcement learning approach to gas turbine control. In Proc. of the 20th Int. Joint Conf. on Neural Networks, Orlando, 2007. MIT Press.
3. M. Heger. Consideration of risk in reinforcement learning. In Proc. of the 11th Int. Conf. on Machine Learning, pages 105-111. Morgan Kaufmann, 1994.
4. R. Neuneier and O. Mihatsch. Risk sensitive reinforcement learning. In Proc. of the 11th Annual Conf. on Neural Information Processing Systems, pages 1031-1037, 1998.
5. P. Geibel. Reinforcement learning with bounded risk. In Proc. of the 18th Int. Conf. on Machine Learning, pages 162-169. Morgan Kaufmann, San Francisco, CA, 2001.
6. P. Abbeel and A.Y. Ng. Exploration and apprenticeship learning in reinforcement learning. In Proc. of the 22nd Int. Conf. on Machine Learning, pages 1-8, 2005.
7. M. Riedmiller. Neural fitted q-iteration - first experiences with a data efficient neural reinforcement learning method. In Proc. of the 16th European Conf. on Machine Learning, pages 317-328, 2005.