Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.04938 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914273394950144 |
|---|---|
| author | Jin, Yuxin Wang, Haotian Yao, Wang Zhang, Xiao |
| author_facet | Jin, Yuxin Wang, Haotian Yao, Wang Zhang, Xiao |
| contents | In this paper, an initial error tolerant distributed mean field control method under partial and discrete information is introduced, where each agent only has discrete observations on its own state. First, we study agents' behavior in linear quadratic mean field games (LQMFGs) under heterogeneous erroneous information of the initial mean field state (MF-S), and formulate the relationships between initial errors and systemic deviations. Next, by capturing the initial error affection on the private trajectory of an agent, we give a distributed error estimation method based on maximum likelihood estimation (MLE), where each agent estimates information errors only based on discrete observations on its private trajectory. Furthermore, we establish an error-based segmented state estimation method, design the initial error tolerant distributed mean field control method (IET-DMFC), and demonstrate the consistent property of state estimation as observation frequency increases. Finally, simulations are performed to verify the efficiency of the algorithm and the consistent properties. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_04938 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Initial Error Tolerant Distributed Mean Field Control under Partial and Discrete Information Jin, Yuxin Wang, Haotian Yao, Wang Zhang, Xiao Optimization and Control In this paper, an initial error tolerant distributed mean field control method under partial and discrete information is introduced, where each agent only has discrete observations on its own state. First, we study agents' behavior in linear quadratic mean field games (LQMFGs) under heterogeneous erroneous information of the initial mean field state (MF-S), and formulate the relationships between initial errors and systemic deviations. Next, by capturing the initial error affection on the private trajectory of an agent, we give a distributed error estimation method based on maximum likelihood estimation (MLE), where each agent estimates information errors only based on discrete observations on its private trajectory. Furthermore, we establish an error-based segmented state estimation method, design the initial error tolerant distributed mean field control method (IET-DMFC), and demonstrate the consistent property of state estimation as observation frequency increases. Finally, simulations are performed to verify the efficiency of the algorithm and the consistent properties. |
| title | Initial Error Tolerant Distributed Mean Field Control under Partial and Discrete Information |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2504.04938 |