Learning in “Do-It-Yourself Lottery” with Full Information: A Computational Study
Learning in “Do-It-Yourself Lottery” with Full Information: A Computational Study
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在完整信息的“DIY 彩票”中学习：一项计算研究
DOI：
10.1007/978-4-431-54279-7_17
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发表时间：
2013
影响因子：
2.3
通讯作者：
T. Terano
中科院分区：
文献类型：
--
作者：
Takashi Yamada;T. Terano
本文利用基于主体的计算经济学方法研究了巴罗的“自己动手买彩票”中基于信念的学习模型所导致的参与者的动态行为。彩票是玩家选择一个预期最小的正整数，但没有其他人选择。为此，我们考虑一个简单的游戏形式，其中每个玩家都知道所有玩家的提交在他们的决策时。我们使用计算机模拟来改变游戏设置和学习模型的参数。我们的主要发现有两个方面：第一，提交和获胜整数的分布在许多情况下与均衡中的分布不同。其次，游戏模式取决于学习模型和游戏设置本身中的两个参数：虽然较低的敏感性参数值通常会导致某种程度上的随机行为，但在较高敏感性参数的情况下，集体行为是单一模式或多个模式。
We study the kind of dynamics players using a belief-based learning model lead to in Barrow’s “do-it-yourself lottery” by an agent-based computational economics approach. The lottery is that players choose a positive integer that is expected to be the smallest, but no one else chooses. For this purpose, we consider a simple game form in which every player knows all players’ submissions at the time of their decision making. We use computer simulations to change the game setup and the parameters of the learning model. Our main findings are twofold: First, the distributions of the submitted and winning integers are different from those in equilibrium in many cases. Second, the game patterns are contingent upon the two parameters in the learning model and the game setup itself: While a lower-sensitivity parameter value often leads to a somewhat randomized behavior, in the case of a higher-sensitivity parameter, the collective behavior is either a single pattern or plural ones.