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pro vyhledávání: '"Thomas, Albert"'
We address offline reinforcement learning with privacy guarantees, where the goal is to train a policy that is differentially private with respect to individual trajectories in the dataset. To achieve this, we introduce DP-MORL, an MBRL algorithm com
Externí odkaz:
http://arxiv.org/abs/2402.05525
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning
In model-based reinforcement learning, most algorithms rely on simulating trajectories from one-step models of the dynamics learned on data. A critical challenge of this approach is the compounding of one-step prediction errors as the length of the t
Externí odkaz:
http://arxiv.org/abs/2402.03146
We consider the problem of offline reinforcement learning where only a set of system transitions is made available for policy optimization. Following recent advances in the field, we consider a model-based reinforcement learning algorithm that infers
Externí odkaz:
http://arxiv.org/abs/2402.02858
In model-based reinforcement learning (MBRL), most algorithms rely on simulating trajectories from one-step dynamics models learned on data. A critical challenge of this approach is the compounding of one-step prediction errors as length of the traje
Externí odkaz:
http://arxiv.org/abs/2310.05672
Publikováno v:
Smart and Sustainable Built Environment, 2023, Vol. 13, Issue 5, pp. 1213-1239.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SASBE-09-2022-0210
Autor:
C. Antonia Klöcker, Ole Thomas Albert, Keno Ferter, Otte Bjelland, Robert J. Lennox, Jon Albretsen, Lotte Pohl, Lotte Svengård Dahlmo, Nuno Queiroz, Claudia Junge
Publikováno v:
Movement Ecology, Vol 12, Iss 1, Pp 1-21 (2024)
Abstract Background Studying habitat use and vertical movement patterns of individual fish over continuous time and space is innately challenging and has therefore largely remained elusive for a wide range of species. Amongst sharks, this applies par
Externí odkaz:
https://doaj.org/article/feb01499dfa64cde90dcc39e3cc53275