Learning adaptive control in dynamic environments using reproducing kernel priors with bayesian policy gradients-Reference-Cited by-同舟云学术

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Learning adaptive control in dynamic environments using reproducing kernel priors with bayesian policy gradients

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
language:
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Author:

Dastider Apan¹,Raza Sayyed Jaffar Ali¹,Lin Mingjie¹

Affiliation:

1. University of Central Florida

Funder

National Science Foundation

Defense University Research Instrumentation Program (DURIP), US

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477314.3507091

Reference29 articles.

1. Quantifying demographic uncertainty: Bayesian methods for integral projection models;Elderd Bret D;Ecological Monographs,2016

2. Bayesian policy gradient algorithms;Engel Yaakov;Advances in NIPS,2007

3. Probabilistic policy reuse in a reinforcement learning agent

4. Meta-learning shared strategies;Frans Kevin;OpenAI. Iclr,2018

5. Bayesian {Monte Carlo};Ghahramani Zoubin;Advances in NIPS,2002

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