Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 1432-1439.
Abstract
Control applications often feature tasks with similar, but not identical, dynamics. We introduce the Hidden Parameter Markov Decision Process (HiP-MDP), a framework that parametrizes a family of related dynamical systems with a low-dimensional set of latent factors, and introduce a semiparametric regression approach for learning its structure from data. We show that a learned HiP-MDP rapidly identifies the dynamics of new task instances in several settings, flexibly adapting to task variation.
Finale Doshi-Velez, and George Dimitri Konidaris. 2016. Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 1432–1439. https://ijcai.org/proceedings/2016/206
Doshi-Velez, F., & Konidaris, G. D. (2016). Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 (pp. 1432–1439). IJCAI. https://ijcai.org/proceedings/2016/206
@inproceedings{ijcai2016p206,
title = {Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations},
author = {Doshi-Velez, Finale and Konidaris, George Dimitri},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {1432--1439},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/206},
}
TY - CPAPER TI - Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations AU - Doshi-Velez, Finale AU - Konidaris, George Dimitri T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 1432 EP - 1439 UR - https://ijcai.org/proceedings/2016/206 ER -Copied
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