ML Anthology

SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes

Balaraman Ravindran, Andrew G. Barto
IJCAI 2003 pp. 1011-1018
/ijcai/2003/ravindran2003ijcai-smdp/

Abstract

To operate effectively in complex environments learning agents require the ability to selectively ignore irrelevant details and form useful abstractions.

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Text

Ravindran and Barto. "SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes." International Joint Conference on Artificial Intelligence, 2003.

Markdown

[Ravindran and Barto. "SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes." International Joint Conference on Artificial Intelligence, 2003.](https://mlanthology.org/ijcai/2003/ravindran2003ijcai-smdp/)

BibTeX

@inproceedings{ravindran2003ijcai-smdp,
  title     = {{SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes}},
  author    = {Ravindran, Balaraman and Barto, Andrew G.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2003},
  pages     = {1011-1018},
  url       = {https://mlanthology.org/ijcai/2003/ravindran2003ijcai-smdp/}
}