Path Integral Control and State Dependent Feedback
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Abstract (arXiv)
In this paper we address the problem to compute state dependent feedback controls for path integral control problems. To this end we generalize the path integral control formula and utilize this to construct parameterized state dependent feedback controllers. In addition, we show a novel relation between control and importance sampling: better control, in terms of control cost, yields more efficient importance sampling, in terms of effective sample size. The optimal control provides a zero-variance estimate.
Key facts. Cited by 11 papers in the map (data through 13 Oct 2026). First posted on arXiv 16 Jun 2014.
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Citing papers per year: 2021: 3; 2022: 4; 2023: 0; 2024: 3; 2025: 0; 2026: 1.
11 papers.
- 2021Path Integral Sampler: a stochastic control approach for samplingcited by 178
- 2022An optimal control perspective on diffusion-based generative modelingcited by 146
- 2021Bayesian Learning via Neural Schr"odinger-F"ollmer Flowscited by 56
- 2022Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Pathscited by 36
- 2024Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inferencecited by 16
- 2021Reinforcement learning of rare diffusive dynamicscited by 15
- 2022Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusionscited by 4
- 2022Deriving time-averaged active inference from control principlescited by 1
- 2024Myopically Verifiable Probabilistic Certificates for Safe Control and Learningcited by 1
- 2024Control, Transport and Sampling: Towards Better Loss Designcited by 0
- 2026Path Integral Value Matching for Linear Quadratic Stochastic Optimal Controlcited by 0
- 2026Path Integral Value Matching for Linear Quadratic Stochastic Optimal Control11 Aug 2026
- 2024Control, Transport and Sampling: Towards Better Loss Design22 May 2024
- 2024Myopically Verifiable Probabilistic Certificates for Safe Control and Learning23 Apr 2024
- 2024Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference6 Mar 2024
- 2022An optimal control perspective on diffusion-based generative modeling2 Nov 2022
- 2022Deriving time-averaged active inference from control principles22 Aug 2022
- 2022Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths27 Jun 2022
- 2022Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions7 Jun 2022
- 2021Path Integral Sampler: a stochastic control approach for sampling30 Nov 2021
- 2021Bayesian Learning via Neural Schr"odinger-F"ollmer Flows20 Nov 2021
- 2021Reinforcement learning of rare diffusive dynamics10 May 2021