MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909160827781120 |
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| author | Altmann, Philipp Winter, Katharina Kölle, Michael Zorn, Maximilian Phan, Thomy Linnhoff-Popien, Claudia |
| author_facet | Altmann, Philipp Winter, Katharina Kölle, Michael Zorn, Maximilian Phan, Thomy Linnhoff-Popien, Claudia |
| contents | Recent advances in multi-agent systems (MAS) have shown that incorporating peer incentivization (PI) mechanisms vastly improves cooperation. Especially in social dilemmas, communication between the agents helps to overcome sub-optimal Nash equilibria. However, incentivization tokens need to be carefully selected. Furthermore, real-world applications might yield increased privacy requirements and limited exchange. Therefore, we extend the PI protocol for mutual acknowledgment token exchange (MATE) and provide additional analysis on the impact of the chosen tokens. Building upon those insights, we propose mutually endorsed distributed incentive acknowledgment token exchange (MEDIATE), an extended PI architecture employing automatic token derivation via decentralized consensus. Empirical results show the stable agreement on appropriate tokens yielding superior performance compared to static tokens and state-of-the-art approaches in different social dilemma environments with various reward distributions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03431 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange Altmann, Philipp Winter, Katharina Kölle, Michael Zorn, Maximilian Phan, Thomy Linnhoff-Popien, Claudia Multiagent Systems Recent advances in multi-agent systems (MAS) have shown that incorporating peer incentivization (PI) mechanisms vastly improves cooperation. Especially in social dilemmas, communication between the agents helps to overcome sub-optimal Nash equilibria. However, incentivization tokens need to be carefully selected. Furthermore, real-world applications might yield increased privacy requirements and limited exchange. Therefore, we extend the PI protocol for mutual acknowledgment token exchange (MATE) and provide additional analysis on the impact of the chosen tokens. Building upon those insights, we propose mutually endorsed distributed incentive acknowledgment token exchange (MEDIATE), an extended PI architecture employing automatic token derivation via decentralized consensus. Empirical results show the stable agreement on appropriate tokens yielding superior performance compared to static tokens and state-of-the-art approaches in different social dilemma environments with various reward distributions. |
| title | MEDIATE: Mutually Endorsed Distributed Incentive Acknowledgment Token Exchange |
| topic | Multiagent Systems |
| url | https://arxiv.org/abs/2404.03431 |