Token Economy for Fair and Efficient Dynamic Resource Allocation in Congestion Games
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866911528019558400 |
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| author | Pedroso, Leonardo Agazzi, Andrea Heemels, W. P. M. H. Salazar, Mauro |
| author_facet | Pedroso, Leonardo Agazzi, Andrea Heemels, W. P. M. H. Salazar, Mauro |
| contents | Self-interested behavior in sharing economies often leads to inefficient aggregate outcomes compared to a centrally coordinated allocation, ultimately harming users. Yet, centralized coordination removes individual decision power. This issue can be addressed by designing rules that align individual preferences with system-level objectives. Unfortunately, rules based on conventional monetary mechanisms introduce unfairness by discriminating among users based on their wealth. To solve this problem, in this paper, we propose a token-based mechanism for congestion games that achieves efficient and fair dynamic resource allocation. Specifically, we model the token economy as a continuous-time dynamic game with finitely many boundedly rational agents, explicitly capturing their evolutionary policy-revision dynamics. We derive a mean-field approximation of the finite-population game and establish strong approximation guarantees between the mean-field and the finite-population games. This approximation enables the design of integer tolls in closed form that provably steer the aggregate dynamics toward an optimal efficient and fair allocation from any initial condition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18094 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Token Economy for Fair and Efficient Dynamic Resource Allocation in Congestion Games Pedroso, Leonardo Agazzi, Andrea Heemels, W. P. M. H. Salazar, Mauro Computer Science and Game Theory Systems and Control Self-interested behavior in sharing economies often leads to inefficient aggregate outcomes compared to a centrally coordinated allocation, ultimately harming users. Yet, centralized coordination removes individual decision power. This issue can be addressed by designing rules that align individual preferences with system-level objectives. Unfortunately, rules based on conventional monetary mechanisms introduce unfairness by discriminating among users based on their wealth. To solve this problem, in this paper, we propose a token-based mechanism for congestion games that achieves efficient and fair dynamic resource allocation. Specifically, we model the token economy as a continuous-time dynamic game with finitely many boundedly rational agents, explicitly capturing their evolutionary policy-revision dynamics. We derive a mean-field approximation of the finite-population game and establish strong approximation guarantees between the mean-field and the finite-population games. This approximation enables the design of integer tolls in closed form that provably steer the aggregate dynamics toward an optimal efficient and fair allocation from any initial condition. |
| title | Token Economy for Fair and Efficient Dynamic Resource Allocation in Congestion Games |
| topic | Computer Science and Game Theory Systems and Control |
| url | https://arxiv.org/abs/2603.18094 |