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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.08222 |
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| _version_ | 1866910116574396416 |
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| author | Shafiei, Arash Rodrigues, Caio César Graciani Russo, Giovanni |
| author_facet | Shafiei, Arash Rodrigues, Caio César Graciani Russo, Giovanni |
| contents | We present a variational free-energy formulation for distributionally robust decision-making with ambiguity in the generative model. The formulation, related to a broad range of learning and control frameworks, yields a minimax optimal control problem where maximization is over an uncertainty set that represents ambiguities. We prove that computing the optimal policy requires solving a non-convex minimization problem and propose an algorithm with convergence guarantees to find the solution. The effectiveness of our results is illustrated via simulations on a pendulum swing-up problem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_08222 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Free-Energy Minimizing Policies Under Generative Model Ambiguity Shafiei, Arash Rodrigues, Caio César Graciani Russo, Giovanni Optimization and Control We present a variational free-energy formulation for distributionally robust decision-making with ambiguity in the generative model. The formulation, related to a broad range of learning and control frameworks, yields a minimax optimal control problem where maximization is over an uncertainty set that represents ambiguities. We prove that computing the optimal policy requires solving a non-convex minimization problem and propose an algorithm with convergence guarantees to find the solution. The effectiveness of our results is illustrated via simulations on a pendulum swing-up problem. |
| title | Free-Energy Minimizing Policies Under Generative Model Ambiguity |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2604.08222 |