2 citations · 2 across the 3 of their papers we have counts for
3 papers
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning
Abdelhakim Benechehab, Albert Thomas, Giuseppe Paolo +2
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 i…
Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning
Abdelhakim Benechehab, Albert Thomas, Balázs Kégl
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,…
Multi-timestep models for Model-based Reinforcement Learning
Abdelhakim Benechehab, Giuseppe Paolo, Albert Thomas +2
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 i…