论文标题
重复关键字拍卖中有关人类友好策略的推理
Reasoning about Human-Friendly Strategies in Repeated Keyword Auctions
论文作者
论文摘要
在在线广告中，搜索引擎通过拍卖不断出售关键字的广告位置。该问题可以看作是无限重复的游戏，因为每当用户使用关键字进行查询时，拍卖就会执行。由于广告商可能经常改变投标，因此游戏将具有大量的平衡，并具有潜在的复杂策略。在本文中，我们建议使用自然策略在这种环境下进行推理，因为它们是由具有有限记忆力和/或计算能力的人工代理人处理的，并且人类用户可以理解。为了实现这一目标，我们在不完美的信息的情况下引入了具有自然策略的策略逻辑的定量版本。第一步，我们展示了如何为重复的关键字拍卖建模策略，并利用模型来证明评估该游戏的属性。在第二步中，我们研究了有或没有召回的策略，研究了与区别能力，表现力和模型检查复杂性有关的逻辑。
In online advertising, search engines sell ad placements for keywords continuously through auctions. This problem can be seen as an infinitely repeated game since the auction is executed whenever a user performs a query with the keyword. As advertisers may frequently change their bids, the game will have a large set of equilibria with potentially complex strategies. In this paper, we propose the use of natural strategies for reasoning in such setting as they are processable by artificial agents with limited memory and/or computational power as well as understandable by human users. To reach this goal, we introduce a quantitative version of Strategy Logic with natural strategies in the setting of imperfect information. In a first step, we show how to model strategies for repeated keyword auctions and take advantage of the model for proving properties evaluating this game. In a second step, we study the logic in relation to the distinguishing power, expressivity, and model-checking complexity for strategies with and without recall.
