Showing cs.AIShow all
2 papers · 1 filter
cs.AI2026
Advantage-Guided Diffusion for Model-Based Reinforcement Learning
Daniele Foffano, Arvid Eriksson, David Broman +2
Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world models mitigate this by generating trajectory se…
cs.AI2026
Receding-Horizon Control via Drifting Models
Daniele Foffano, Alessio Russo, Alexandre Proutiere
We study the problem of trajectory optimization in settings where the system dynamics are unknown and it is not possible to simulate trajectories through a surrogate model. When an…