@inproceedings{kim2011cpbvi,
author = {Kim, Dongho and Lee, Jaesong and Kim, Kee-Eung and Poupart, Pascal},
title = {Point-Based Value Iteration for Constrained POMDPs},
year = {2011},
isbn = {9781577355151},
publisher = {AAAI Press},
abstract = {Constrained partially observable Markov decision processes (CPOMDPs) extend the standard POMDPs by allowing the specification of constraints on some aspects of the policy in addition to the optimality objective for the value function. CPOMDPs have many practical advantages over standard POMDPs since they naturally model problems involving limited resource or multiple objectives. In this paper, we show that the optimal policies in CPOMDPs can be randomized, and present exact and approximate dynamic programming methods for computing randomized optimal policies. While the exact method requires solving a minimax quadratically constrained program (QCP) in each dynamic programming update, the approximate method utilizes the point-based value update with a linear program (LP). We show that the randomized policies are significantly better than the deterministic ones. We also demonstrate that the approximate point-based method is scalable to solve large problems.},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume Three},
pages = {1968–1974},
numpages = {7},
location = {Barcelona, Catalonia, Spain},
series = {IJCAI'11}
}

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publisher = {AUAI Press},
address = {Arlington, Virginia, USA},
booktitle = {Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence},
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numpages = {8},
location = {Banff, Canada},
series = {UAI '04}
}

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year = {2021},
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publisher = {AI Access Foundation},
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numpages = {47}
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    AUTHOR    = {Hanna Kurniawati and David Hsu and Wee Sun Lee},
    TITLE     = {{SARSOP}: Efficient Point-Based {POMDP} Planning by Approximating Optimally Reachable Belief Spaces},
    BOOKTITLE = {Proceedings of Robotics: Science and Systems IV},
    YEAR      = {2008},
    ADDRESS   = {Zurich, Switzerland},
    MONTH     = {June}
}

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  year={2008}
}

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 author = {Lee, Jongmin and Kim, Geon-hyeong and Poupart, Pascal and Kim, Kee-Eung},
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@InProceedings{kalagarla22aNoRegret,
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  author =       {Kalagarla, Krishna C. and Dhruva, Kartik and Shen, Dongming and Jain, Rahul and Nayyar, Ashutosh and Nuzzo, Pierluigi},
  booktitle = 	 {Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence},
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  volume = 	 {180},
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@INPROCEEDINGS{Wray2022pga,
  author={Wray, Kyle Hollins and Czuprynski, Kenneth},
  booktitle={2022 International Conference on Robotics and Automation (ICRA)}, 
  title={Scalable Gradient Ascent for Controllers in Constrained POMDPs}, 
  year={2022},
  volume={},
  number={},
  pages={9085-9091}}
