ML Anthology

Towards Scalable MDP Algorithms

Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2011 pp. 2818-2819
doi:10.5591/978-1-57735-516-8/IJCAI11-481 /ijcai/2011/kolobov2011ijcai-scalable/

Abstract

The scalability of algorithms for solving Markov Decision Processes (MDPs) has been a limiting factor for MDPs as a modeling tool. This dissertation develops theoretical and empirical techniques for solving larger MDPs than was possible before, and aims to demonstrate the achieved progress by applying these new algorithms to a real-world problem.

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Text

Kolobov et al. "Towards Scalable MDP Algorithms." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-481

Markdown

[Kolobov et al. "Towards Scalable MDP Algorithms." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/kolobov2011ijcai-scalable/) doi:10.5591/978-1-57735-516-8/IJCAI11-481

BibTeX

@inproceedings{kolobov2011ijcai-scalable,
  title     = {{Towards Scalable MDP Algorithms}},
  author    = {Kolobov, Andrey and Mausam,  and Weld, Daniel S.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2011},
  pages     = {2818-2819},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-481},
  url       = {https://mlanthology.org/ijcai/2011/kolobov2011ijcai-scalable/}
}