Solving Time-Continuous Stochastic Optimal Control Problems: Algorithm Design and Convergence Analysis of Actor-Critic Flow
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866915118641577984 |
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| author | Zhou, Mo Lu, Jianfeng |
| author_facet | Zhou, Mo Lu, Jianfeng |
| contents | We propose an actor-critic framework to solve the time-continuous stochastic optimal control problem. A least square temporal difference method is applied to compute the value function for the critic. The policy gradient method is implemented as policy improvement for the actor. Our key contribution lies in establishing a linear rate of convergence for our proposed actor-critic flow. Theoretical findings are further validated through numerical examples, showing the efficacy of our approach in practical applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_17208 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Solving Time-Continuous Stochastic Optimal Control Problems: Algorithm Design and Convergence Analysis of Actor-Critic Flow Zhou, Mo Lu, Jianfeng Optimization and Control 93E20 (Primary), 49L12 49M25 (secondary) G.1.6; G.1.8 We propose an actor-critic framework to solve the time-continuous stochastic optimal control problem. A least square temporal difference method is applied to compute the value function for the critic. The policy gradient method is implemented as policy improvement for the actor. Our key contribution lies in establishing a linear rate of convergence for our proposed actor-critic flow. Theoretical findings are further validated through numerical examples, showing the efficacy of our approach in practical applications. |
| title | Solving Time-Continuous Stochastic Optimal Control Problems: Algorithm Design and Convergence Analysis of Actor-Critic Flow |
| topic | Optimization and Control 93E20 (Primary), 49L12 49M25 (secondary) G.1.6; G.1.8 |
| url | https://arxiv.org/abs/2402.17208 |