Learning by similarity-weighted imitation in winner-takes-all games

• 成果类型: Article
• 署名作者: Mohlin, Erik; Ostling, Robert; Wang, Joseph Tao-yi
• 署名单位: Lund University; Stockholm School of Economics; National Taiwan University
• 刊物名称: GAMES AND ECONOMIC BEHAVIOR
• ISSN/ISSBN: 0899-8256
• DOI: 10.1016/j.geb.2019.12.008
• 发表日期: 2020
• 页码: 225-245
• 关键词: Learning; imitation; Behavioral game theory; evolutionary game theory; stochastic approximation; Replicator dynamic; Similarity-based reasoning; Beauty contest; Lowest unique positive integer game; Mixed equilibrium

摘要

We study a simple model of similarity-based global cumulative imitation in symmetric games with large and ordered strategy sets and a salient winning player. We show that the learning model explains behavior well in both field and laboratory data from one such winner-takes-all game: the lowest unique positive integer game in which the player that chose the lowest number not chosen by anyone else wins a fixed prize. We corroborate this finding in three other winner-takes-all games and discuss under what conditions the model may be applicable beyond this class of games. Theoretically, we show that global cumulative imitation without similarity weighting results in a version of the replicator dynamic in winner-takes-all games. (C) 2020 Elsevier Inc. All rights reserved.