Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs

Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass. Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. In Joost N. Kok, Jacek Koronacki, Ramon López de Mántaras, Stan Matwin, Dunja Mladenic, Andrzej Skowron, editors, Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings. Volume 4701 of Lecture Notes in Computer Science, pages 250-261, Springer, 2007. [doi]

@inproceedings{NeumannPM07,
  title = {Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs},
  author = {Gerhard Neumann and Michael Pfeiffer and Wolfgang Maass},
  year = {2007},
  doi = {10.1007/978-3-540-74958-5_25},
  url = {http://dx.doi.org/10.1007/978-3-540-74958-5_25},
  tags = {graph-rewriting, rewriting},
  researchr = {https://researchr.org/publication/NeumannPM07},
  cites = {0},
  citedby = {0},
  pages = {250-261},
  booktitle = {Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings},
  editor = {Joost N. Kok and Jacek Koronacki and Ramon López de Mántaras and Stan Matwin and Dunja Mladenic and Andrzej Skowron},
  volume = {4701},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-540-74957-8},
}