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English(EN) AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games

新的AGiR框架旨在解决多智能体博弈中过度依赖礼物的问题

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种名为AGiR的新框架，旨在解决混合动机博弈中过度依赖礼物的问题。当博弈中的智能体过度依赖礼物时，就会出现这个问题，阻碍它们学习独立产生奖励的行为。AGiR实施了一种自适应拒绝机制，允许智能体选择性地拒绝礼物，从而缓解过度依赖并防止被剥削。该框架在各种环境和赠送方案中持续提高了 $\alpha$-公平性，而无需对现有训练流程进行重大更改。 AI

影响 这项研究可以提高多智能体系统在竞争和合作环境中的鲁棒性和公平性。

排序理由 该集群包含一篇详细介绍多智能体系统新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的AGiR框架旨在解决多智能体博弈中过度依赖礼物的问题

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该集群包含一篇详细介绍多智能体系统新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Youngchul Sung ·

    AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games

    In this paper, we consider mixed-motive games (MMGs) which model various real-world multi-agent scenarios where self-interested agents must both cooperate and compete. We identify an issue with existing gifting methods, where agents become overly dependent on incoming gifts and f…

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