PI-MPC turns finite-horizon optimal control into inference over a Boltzmann-weighted control distribution and generates actions via variational inference, with MPPI as a key sampling-based example.
Variational inference MPC for Bayesian model- based reinforcement learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Model Predictive Control via Probabilistic Inference: A Tutorial and Survey
PI-MPC turns finite-horizon optimal control into inference over a Boltzmann-weighted control distribution and generates actions via variational inference, with MPPI as a key sampling-based example.