Planning with abstract markov decision processes. Gopalan, N., desJardins , M., Littman, M. L., MacGlashan, J., Squire, S., Tellex, S., Winder, J., & Wong, L. L. S. In International Conference on Automated Planning and Scheduling, pages 480–488, 2017. Paper bibtex @inproceedings{Gopalan2017,
added-at = {2020-05-24T20:36:48.000+0200},
author = {Gopalan, Nakul and desJardins, Marie and Littman, Michael L. and MacGlashan, James and Squire, Shawn and Tellex, Stefanie and Winder, John and Wong, Lawson L. S.},
biburl = {https://www.bibsonomy.org/bibtex/2ae883357d73d9ce8ec436e599fceaf15/marcondg},
booktitle = {International Conference on Automated Planning and Scheduling},
comment = {Requires domain knowledge for the hierarchical decomposition.
Faster than MAXQ - but MAXQ has more general optimality guarantees, and is model free.
Goal-based: binary goal-based reward (1) if reached goal state, (0) otherwise.
Box-pushing real-world Turtlebot.},
interhash = {21a6568464827fb7346361d30e920772},
intrahash = {ae883357d73d9ce8ec436e599fceaf15},
keywords = {hierarchical, mdp, probabilistic},
pages = {480--488},
timestamp = {2020-05-24T20:36:48.000+0200},
title = {{Planning with abstract markov decision processes}},
url = {https://pdfs.semanticscholar.org/2fa6/b3f543d9b934069fd2f083535638bbc2486d.pdf},
year = 2017
}
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