no code implementations • 5 Feb 2024 • Abdelhakim Benechehab, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Balázs Kégl
In model-based reinforcement learning, most algorithms rely on simulating trajectories from one-step models of the dynamics learned on data.
no code implementations • 5 Feb 2024 • 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.
no code implementations • 9 Oct 2023 • Abdelhakim Benechehab, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl
In model-based reinforcement learning (MBRL), most algorithms rely on simulating trajectories from one-step dynamics models learned on data.
Model-based Reinforcement Learning reinforcement-learning +1