Competing Bandits: The Perils of Exploration Under Competition
Competing Bandits: The Perils of Exploration Under Competition
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强盗竞争：竞争中探索的危险
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Zhiwei Steven Wu
中科院分区：
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作者：
Guy Aridor;Y. Mansour;Aleksandrs Slivkins;Zhiwei Steven Wu
大多数在线平台都努力从与消费者的互动中学习，并且许多平台都进行探索：为了获取新信息而做出潜在的次优选择。我们发起了一项关于探索和竞争之间相互作用的研究：这些平台如何平衡学习探索和消费者竞争。在这里，消费者扮演着三个不同的角色：他们是产生收入的客户，他们是学习数据的来源，他们是在竞争平台中进行选择的自利代理人。我们考虑一个程式化的双头垄断模型，其中两家公司面临相同的多臂强盗实例。用户一一到达并在两家公司之间进行选择，这样每个公司只有在被选择的情况下才能在其强盗实例上取得进展。我们研究竞争是否以及在多大程度上刺激了更好的强盗算法的采用，以及它是否会导致消费者福利的增加。我们发现，激烈的竞争会促使企业采用“贪婪”的强盗算法，从而导致消费者福利较低。然而，我们发现，通过为企业提供一些“免费”消费者来削弱竞争可以激励更好的探索策略并增加消费者福利。我们研究了削弱竞争的两种途径：放松消费者的理性和给予企业先发优势。我们提供理论结果和数值模拟的组合。我们的发现与“竞争与创新”关系密切相关，这是经济学中一个经过深入研究的主题。他们还通过探索数据作为进入在线市场的障碍所发挥的作用，阐明了数字经济的先发优势。
Most online platforms strive to learn from interactions with consumers, and many engage in exploration: making potentially suboptimal choices for the sake of acquiring new information. We initiate a study of the interplay between exploration and competition: how such platforms balance the exploration for learning and the competition for consumers. Here consumers play three distinct roles: they are customers that generate revenue, they are sources of data for learning, and they are self-interested agents which choose among the competing platforms. We consider a stylized duopoly model in which two firms face the same multi-armed bandit instance. Users arrive one by one and choose between the two firms, so that each firm makes progress on its bandit instance only if it is chosen. We study whether and to what extent competition incentivizes the adoption of better bandit algorithms, and whether it leads to welfare increases for consumers. We find that stark competition induces firms to commit to a "greedy" bandit algorithm that leads to low consumer welfare. However, we find that weakening competition by providing firms with some "free" consumers incentivizes better exploration strategies and increases consumer welfare. We investigate two channels for weakening the competition: relaxing the rationality of consumers and giving one firm a first-mover advantage. We provide a mix of theoretical results and numerical simulations. Our findings are closely related to the "competition vs. innovation" relationship, a well-studied theme in economics. They also elucidate the first-mover advantage in the digital economy by exploring the role that data can play as a barrier to entry in online markets.