A stochastic Pontryagin maximum principle on the Sierpinski gasket
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arXiv
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| Format: | Preprint |
| Publié: |
2017
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| _version_ | 1866909340298903552 |
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| author | Liu, Xuan |
| author_facet | Liu, Xuan |
| contents | In this paper, we consider stochastic control problems on the Sierpinski gasket. An order comparison lemma is derived using heat kernel estimate for Brownian motion on the gasket. Using the order comparison lemma and techniques of BSDEs, we establish a Pontryagin stochastic maximum principle for these control problems. It turns out that the stochastic maximum principle on the Sierpinski gasket involves two necessity equations in contrast to its counterpart on Euclidean spaces. This effect is due to singularity between the Hausdorff measure and the energy dominant measure on the gasket, which is a common feature shared by many fractal spaces. The linear regulator problems on the gasket is also considered as an example. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1701_02563 |
| institution | arXiv |
| publishDate | 2017 |
| record_format | arxiv |
| spellingShingle | A stochastic Pontryagin maximum principle on the Sierpinski gasket Liu, Xuan Probability Optimization and Control In this paper, we consider stochastic control problems on the Sierpinski gasket. An order comparison lemma is derived using heat kernel estimate for Brownian motion on the gasket. Using the order comparison lemma and techniques of BSDEs, we establish a Pontryagin stochastic maximum principle for these control problems. It turns out that the stochastic maximum principle on the Sierpinski gasket involves two necessity equations in contrast to its counterpart on Euclidean spaces. This effect is due to singularity between the Hausdorff measure and the energy dominant measure on the gasket, which is a common feature shared by many fractal spaces. The linear regulator problems on the gasket is also considered as an example. |
| title | A stochastic Pontryagin maximum principle on the Sierpinski gasket |
| topic | Probability Optimization and Control |
| url | https://arxiv.org/abs/1701.02563 |