Reimagining Peer Review Process Through Multi-Agent Mechanism Design
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866917225554771968 |
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| author | Farooq, Ahmad Iqbal, Kamran |
| author_facet | Farooq, Ahmad Iqbal, Kamran |
| contents | The software engineering research community faces a systemic crisis: peer review is failing under growing submissions, misaligned incentives, and reviewer fatigue. Community surveys reveal that researchers perceive the process as "broken." This position paper argues that these dysfunctions are mechanism design failures amenable to computational solutions. We propose modeling the research community as a stochastic multi-agent system and applying multi-agent reinforcement learning to design incentive-compatible protocols. We outline three interventions: a credit-based submission economy, MARL-optimized reviewer assignment, and hybrid verification of review consistency. We present threat models, equity considerations, and phased pilot metrics. This vision charts a research agenda toward sustainable peer review. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19778 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Reimagining Peer Review Process Through Multi-Agent Mechanism Design Farooq, Ahmad Iqbal, Kamran Multiagent Systems Artificial Intelligence Computers and Society Computer Science and Game Theory Software Engineering 68T42, 91B26 I.2.11; D.2.9; J.4 The software engineering research community faces a systemic crisis: peer review is failing under growing submissions, misaligned incentives, and reviewer fatigue. Community surveys reveal that researchers perceive the process as "broken." This position paper argues that these dysfunctions are mechanism design failures amenable to computational solutions. We propose modeling the research community as a stochastic multi-agent system and applying multi-agent reinforcement learning to design incentive-compatible protocols. We outline three interventions: a credit-based submission economy, MARL-optimized reviewer assignment, and hybrid verification of review consistency. We present threat models, equity considerations, and phased pilot metrics. This vision charts a research agenda toward sustainable peer review. |
| title | Reimagining Peer Review Process Through Multi-Agent Mechanism Design |
| topic | Multiagent Systems Artificial Intelligence Computers and Society Computer Science and Game Theory Software Engineering 68T42, 91B26 I.2.11; D.2.9; J.4 |
| url | https://arxiv.org/abs/2601.19778 |