Measuring the benefits of lying in MARA under egalitarian social welfare
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866909990282854400 |
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| author | Carrero, Jonathan Rodriguez, Ismael Rubio, Fernando |
| author_facet | Carrero, Jonathan Rodriguez, Ismael Rubio, Fernando |
| contents | When some resources are to be distributed among a set of agents following egalitarian social welfare, the goal is to maximize the utility of the agent whose utility turns out to be minimal. In this context, agents can have an incentive to lie about their actual preferences, so that more valuable resources are assigned to them. In this paper we analyze this situation, and we present a practical study where genetic algorithms are used to assess the benefits of lying under different situations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_09354 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Measuring the benefits of lying in MARA under egalitarian social welfare Carrero, Jonathan Rodriguez, Ismael Rubio, Fernando Computer Science and Game Theory Neural and Evolutionary Computing When some resources are to be distributed among a set of agents following egalitarian social welfare, the goal is to maximize the utility of the agent whose utility turns out to be minimal. In this context, agents can have an incentive to lie about their actual preferences, so that more valuable resources are assigned to them. In this paper we analyze this situation, and we present a practical study where genetic algorithms are used to assess the benefits of lying under different situations. |
| title | Measuring the benefits of lying in MARA under egalitarian social welfare |
| topic | Computer Science and Game Theory Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2601.09354 |