Libros sobre el tema "Reinforcement learning (Machine learning)"

S, Sutton Richard, ed. Reinforcement learning. Boston: Kluwer Academic Publishers, 1992.

Sutton, Richard S. Reinforcement Learning. Boston, MA: Springer US, 1992.

Pack, Kaelbling Leslie, ed. Recent advances in reinforcement learning. Boston: Kluwer Academic, 1996.

Szepesvári, Csaba. Algorithms for reinforcement learning. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

Kaelbling, Leslie Pack. Recent advances in reinforcement learning. Boston: Kluwer Academic, 1996.

Sutton, Richard S. Reinforcement learning: An introduction. Cambridge, Mass: MIT Press, 1998.

Kulkarni, Parag. Reinforcement and systemic machine learning for decision making. Hoboken, NJ: John Wiley & Sons, 2012.

Kulkarni, Parag. Reinforcement and Systemic Machine Learning for Decision Making. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118266502.

Whiteson, Shimon. Adaptive representations for reinforcement learning. Berlin: Springer Verlag, 2010.

IWLCS 2006 (2006 Seattle, Wash.). Learning classifier systems: 10th international workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th international workshop, IWLCS 2007, London, UK, July 8, 2007 : revised selected papers. Berlin: Springer, 2008.

United States. National Aeronautics and Space Administration., ed. Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations. [Houston, Tex.?]: Research Institute for Computing and Information Systems, 1992.

United States. National Aeronautics and Space Administration., ed. Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations: Special approach/docking testcase results. [Houston, Tex.]: Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1993.

Merrick, Kathryn E. Motivated reinforcement learning: Curious characters for multiuser games. New York: Springer, 2009.

Lou, Maher Mary, ed. Motivated reinforcement learning: Curious characters for multiuser games. New York: Springer, 2009.

IEEE, International Symposium on Approximate Dynamic Programming and Reinforcement Learning (1st 2007 Honolulu Hawaii). 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning: Honolulu, HI, 1-5 April 2007. Piscataway, NJ: IEEE, 2007.

Hester, Todd. TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains. Heidelberg: Springer International Publishing, 2013.

IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (1st 2007 Honolulu, Hawaii). 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning: Honolulu, HI, 1-5 April 2007. Piscataway, NJ: IEEE, 2007.

IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (1st 2007 Honolulu, Hawaii). 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning: Honolulu, HI, 1-5 April 2007. Piscataway, NJ: IEEE, 2007.

Jaume, Bacardit y IWLCS 2007 (2007 : London, England), eds. Learning classifier systems: 10th international workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th international workshop, IWLCS 2007, London, UK, July 8, 2007 : revised selected papers. Berlin: Springer, 2008.

IWLCS 2006 (2006 Seattle, Wash.). Learning classifier systems: 10th international workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th international workshop, IWLCS 2007, London, UK, July 8, 2007 : revised selected papers. Berlin: Springer, 2008.

Marcus, Hutter y SpringerLink (Online service), eds. Recent Advances in Reinforcement Learning: 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

Rieser, Verena. Reinforcement Learning for Adaptive Dialogue Systems: A Data-driven Methodology for Dialogue Management and Natural Language Generation. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

Wiering, Marco y Martijn van Otterlo, eds. Reinforcement Learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27645-3.

Sutton, Richard S., ed. Reinforcement Learning. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3618-5.

Sugiyama, Masashi. Statistical Reinforcement Learning. Taylor & Francis Group, 2020.

Sugiyama, Masashi. Statistical Reinforcement Learning. Taylor & Francis Group, 2015.

Morimura, Tetsuro, Masashi Sugiyama y Hirotaka Hachiya. Statistical Reinforcement Learning: Modern Machine Learning Approaches. Taylor & Francis Group, 2012.

Sugiyama, Masashi. Statistical Reinforcement Learning: Modern Machine Learning Approaches. Taylor & Francis Group, 2015.

Sugiyama, Masashi. Statistical Reinforcement Learning: Modern Machine Learning Approaches. Taylor & Francis Group, 2015.

Gureckis, Todd M. y Bradley C. Love. Computational Reinforcement Learning. Editado por Jerome R. Busemeyer, Zheng Wang, James T. Townsend y Ami Eidels. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.5.

Statistical Reinforcement Learning. CRC Press, 2012.

Introduction to Deep Reinforcement Learning. Now Publishers, 2018.

Feldspar, David. Reinforcement Learning: Machine Learning, Gamma, and Inventory Management. Independently Published, 2018.

Sutton, Richard S. y Andrew G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.

Sutton, Richard S., Andrew G. Barto y Francis Bach. Reinforcement Learning: An Introduction. MIT Press, 2018.

Sutton, Richard S. y Andrew G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.

Sutton, Richard S. y Andrew G. Barto. Reinforcement Learning: An Introduction. A Bradford Book, 2018.

Sutton, Richard S., Andrew G. Barto y Francis Bach. Reinforcement Learning: An Introduction. MIT Press, 2018.

Sutton, Richard S. y Andrew G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.

Gatti, Christopher. Design of Experiments for Reinforcement Learning. Springer, 2016.

Gatti, Christopher. Design of Experiments for Reinforcement Learning. Springer, 2014.

Gatti, Christopher. Design of Experiments for Reinforcement Learning. Springer, 2014.

Ghavamzadeh, Mohammad, Shie Mannor, Joelle Pineau y Aviv Tamar. Bayesian Reinforcement Learning: A Survey. Now Publishers, 2015.

Transfer In Reinforcement Learning Domains. Springer, 2009.

Ok, DoKyeong. A study of model-based average reward reinforcement learning. 1996.

Ok, DoKyeong. A study of model-based average reward reinforcement learning. 1996.

Zhang, Wei. Reinforcement learning for job-shop scheduling. 1996.

Schwartz, H. M. Multi-Agent Machine Learning: A Reinforcement Approach. Wiley, 2014.

Schwartz, H. M. Multi-Agent Machine Learning: A Reinforcement Approach. Wiley & Sons, Incorporated, John, 2014.

Schwartz, H. M. Multi-Agent Machine Learning: A Reinforcement Approach. Wiley & Sons, Limited, John, 2014.