Farsi / Persian
NetLogo Models Library:
Public Good is a game that asks each of the players to contribute to a common pool that will then be multiplied by the game leader and redistributed to all players.
The standard economic prediction based on 'rational' behavior is that all individuals will contribute nothing. However, in practice, players show a wide diversity of strategies. This game also allows players to pay to remove money from players who are 'doing too well.'
The game can be used to demonstrate basic multiplication, cooperative behavior, and the evolution of altruism as players negotiate fair play.
At the beginning of the game, all players are given the same amount of money. Each turn begins with players anonymously deciding how much money to contribute to a common pool held by the game leader. Then the game leader collects the money and multiplies it by a number greater than one, and then redistributes this money to all the players. At any point during the game a player may press the "punish the rich" button which takes away one dollar from the presser and one dollar from the richest player. The game continues like this until the game leader decides it is an appropriate time to stop.
To begin the game, have students log into the game by initiating their HubNet clients.
Once all players have logged in, the game leader can press "Go" to make players visible in the public space. Then press "Restart Activity" to give each player their starting amount of money (10$). After pressing "Restart Activity" the players should be asked to move their "fraction-put-in" slider to control the amount of money they want to contribute to the common pool to be collected by the game leader. The game moves through "Take Money"-"Give Money" cycles. "Take Money" collects money from all the players and removes it from their individual accounts; the cumulative amount taken is visible in the "Bank". This turns each player's turtle the color white. Then the money is doubled and redistributed equally to all players by pressing "Give Money." This returns the players to their former color.
Players can press the "pay-1-dollar-to-punish-the-rich" button at any time, which takes one dollar from their accounts but also removes one dollar from the wealthiest players account.
The game leader may choose to end the game after a certain number of turns or after a certain player reaches a specific dollar amount in their account.
"labels-on?" will allow players to see names next to each of the accounts visible in the public viewing space. By turning the labels "off" students can remain anonymous during the game.
Discussion on the following topics may be appropriate for different levels of players:
Try playing the game once with labels "Off" then once with labels "On." Does this change the game play?
Try changing the multiplier that the bank uses to increase the money before it is redistributed.
Here are some references to increase your understanding and appreciation of this game and others like it
Henrich, J. and R. Boyd and S.Bowles and C. Camerer and E.Fehr and H. Gintis and R. McElreath (2001) Cooperation, Reciprocity and Punishment in Fifteen Small-scale Societies," Working Papers 01-01-007, Santa Fe Institute.
Sanfey, A. et al. (2003) The Neural basis of economic decision-making in the ultimatum game. Science 300: 1755-1758.
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Copyright 2003 Uri Wilensky.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.
Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at firstname.lastname@example.org.
This activity and associated models and materials were created as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227.