International Joint Conference on Artificial Intelligence
year
2007
pages
2009--2015
comment
Early MBDP.
Keeps a fixed number of policy trees for each agent at each step.
Employs top-down heuristics to identify the most useful belief states.
---=note-separator=---
Early MBDP. Keeps a fixed number of policy trees for each agent at each step. Employs top-down heuristics to identify the most useful belief states.
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%0 Conference Paper
%1 Sven2007a
%A Seuken, Sven
%A Zilberstein, Shlomo
%B International Joint Conference on Artificial Intelligence
%C Hyderabad, India
%D 2007
%K bottom-up, concurrent, dec-pomdp, decentralized, decision-tree, dp, finite-horizon, heuristic, lim-com, mbdp, nondet-outcomes, partial-obs
%P 2009--2015
%T Memory-Bounded Dynamic Programming for DEC-POMDPs
%U http://rbr.cs.umass.edu/shlomo/papers/SZijcai07.pdf
@inproceedings{Sven2007a,
added-at = {2020-05-24T20:36:48.000+0200},
address = {Hyderabad, India},
author = {Seuken, Sven and Zilberstein, Shlomo},
biburl = {https://www.bibsonomy.org/bibtex/2fe24a05ac34da31b505cba233eee9ebe/marcondg},
booktitle = {International Joint Conference on Artificial Intelligence},
comment = {Early MBDP.
Keeps a fixed number of policy trees for each agent at each step.
Employs top-down heuristics to identify the most useful belief states.
---=note-separator=---
Early MBDP. Keeps a fixed number of policy trees for each agent at each step. Employs top-down heuristics to identify the most useful belief states.},
interhash = {89d220f05e7094653421d945ec52ccb9},
intrahash = {fe24a05ac34da31b505cba233eee9ebe},
keywords = {bottom-up, concurrent, dec-pomdp, decentralized, decision-tree, dp, finite-horizon, heuristic, lim-com, mbdp, nondet-outcomes, partial-obs},
pages = {2009--2015},
timestamp = {2020-05-24T20:36:48.000+0200},
title = {Memory-Bounded Dynamic Programming for {DEC-POMDP}s},
url = {http://rbr.cs.umass.edu/shlomo/papers/SZijcai07.pdf},
year = 2007
}