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Using Bots in Strategizing Group Compositions to Improve Decision-Making Processes

机译：在策略中使用BOTS组合物来改善决策过程

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This paper explores utilization of bots created to play as participants in two games that have relevance in the field of economics. The first game is an iterated version of the prisoner's dilemma that has relevance to decisions requiring trust while conducting business and involves a binary decision. The simulation examines one dimension of the Myers-Briggs personality type and its potential association with strategies that may be employed during an iterated version of the game, leading to different levels of performance. A web-based bot is used for such simulation. Results appear to support the possibility of exploiting personality type in this dimension in the context of similar circumstances. The second game is an iterated power to take game that simulates interactions between taxing authorities (takers) and tax-payers (responders), and involves a continuous set of possible decisions for each stage of the game. A specific Myers-Briggs personality type of specified extremity is embedded into each player bot by randomly generating answers to a version of the Myers-Briggs Type Indicator. These answers are individually associated with preferences and strategies that allow the bots to react to the changing game state according to their personality type. This paper explores the combination of, among other things, team sizes, initial conditions of income tax rates in some of the major economies on different continents, adjudication methods for group decisions, as well as personality type extremity. In a large number of simulations, various group compositions in terms of MBTI personality type are matched up against each other under these conditions, and their performance is ranked for each role. Results appear to suggest that selective recruitment practices based on personality type can enhance performance of both takers and responders and may lead to improvements of certain aspects of economic conditions.
机译：本文探讨了在经济领域具有相关性的两次游戏中扮演的机器人的利用。第一场比赛是囚犯困境的迭代版本，与需要信任的决策有关，在开展业务时涉及二元决定。模拟审查了Myers-Briggs人格类型的一个维度及其与可能在游戏的迭代版本期间采用的策略的潜在关联，从而导致不同的性能水平。基于Web的机器人用于这种模拟。结果似乎支持在类似情况下，在这个维度中利用人格类型的可能性。第二场比赛是迭代权力，可以采取税务机关（援助者）和纳税人（响应者）之间的互动，并涉及比赛每个阶段的一系列可能的决策。特定的MyERS-Briggs人格类型的指定肢体是通过随机生成Myers-Briggs类型指示符版本的答案来嵌入到每个玩家机器人中。这些答案与偏好和策略单独关联，允许机器人根据其个性类型对变化的游戏状态作出反应。本文探讨了不同大陆的一些主要经济体的团队规模，团队规模的初始条件的组合，群体决策的裁决方法以及人格类型的极端。在大量的模拟中，在这些条件下，MBTI人格类型的各种组合物在彼此之间匹配，并且它们的性能为每个作用。结果似乎表明，基于人格类型的选择性招聘实践可以提高援助者和响应者的表现，并可能导致经济条件的某些方面的改进。

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