论文标题
人工预测市场为人类合作提供了新的机会
Artificial prediction markets present a novel opportunity for human-AI collaboration
论文作者
论文摘要
尽管在人工智能领域取得了巨大的成功，但机器驱动的技术仍然遭受重要的局限性，尤其是对于需要从有限数据中获得创造力，计划，常识，直觉或学习的复杂任务。这些限制激发了人机合作的有效方法。我们的工作做出了两个主要贡献。我们对人工预测市场模型进行了彻底的实验，以了解市场参数对基准分类任务模型性能的影响。然后，我们通过仿真证明了外源性剂在市场上的影响，这些外源性药物代表了原始的人类行为。这项工作为一套新型混合人类机器学习算法奠定了基础。
Despite high-profile successes in the field of Artificial Intelligence, machine-driven technologies still suffer important limitations, particularly for complex tasks where creativity, planning, common sense, intuition, or learning from limited data is required. These limitations motivate effective methods for human-machine collaboration. Our work makes two primary contributions. We thoroughly experiment with an artificial prediction market model to understand the effects of market parameters on model performance for benchmark classification tasks. We then demonstrate, through simulation, the impact of exogenous agents in the market, where these exogenous agents represent primitive human behaviors. This work lays the foundation for a novel set of hybrid human-AI machine learning algorithms.
