Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909301377859584 |
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| author | Yahmed, Ahmed Ben Calauzènes, Clément Perchet, Vianney |
| author_facet | Yahmed, Ahmed Ben Calauzènes, Clément Perchet, Vianney |
| contents | In the strategic multi-armed bandit setting, when arms possess perfect information about the player's behavior, they can establish an equilibrium where: 1. they retain almost all of their value, 2. they leave the player with a substantial (linear) regret. This study illustrates that, even if complete information is not publicly available to all arms but is shared among them, it is possible to achieve a similar equilibrium. The primary challenge lies in designing a communication protocol that incentivizes the arms to communicate truthfully. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_17101 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms Yahmed, Ahmed Ben Calauzènes, Clément Perchet, Vianney Artificial Intelligence In the strategic multi-armed bandit setting, when arms possess perfect information about the player's behavior, they can establish an equilibrium where: 1. they retain almost all of their value, 2. they leave the player with a substantial (linear) regret. This study illustrates that, even if complete information is not publicly available to all arms but is shared among them, it is possible to achieve a similar equilibrium. The primary challenge lies in designing a communication protocol that incentivizes the arms to communicate truthfully. |
| title | Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2408.17101 |