Learning in “Do-It-Yourself Lottery” with Full Information: A Computational Study

  • Takashi Yamada
  • Takao Terano
Conference paper
Part of the Agent-Based Social Systems book series (ABSS, volume 10)


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.


Agent-based Computational economics Behavioral game Mixed-strategyequilibrium Belief-based learning 



This chapter was modified and extended from the earlier version presented at the 7th International Workshop on Agent-based Approaches in Economic and Social Complex Systems (AESCS 2012) on January 17–19, 2012. We appreciate the participants, two anonymous referees, and editor-in-chief Prof. Tadahiko Murata for helpful comments and suggestions. Financial support from the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Young Scientists (B) (24710163) (Yamada) and by JSPS and ANR under the Joint Research Project, Japan–France CHORUS Program, “Behavioral and cognitive foundations for agent-based models (becoa)” (Terano), is gratefully acknowledged.


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Copyright information

© Springer Japan 2013

Authors and Affiliations

  1. 1.Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and EngineeringTokyo Institute of TechnologyYokohamaJapan

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