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## NetLogo User Community Models

## WHAT IS IT?
To see what happens when agents play the Ultimatum game, where, depending on their strategies, which are randomly created for the agents, there will be agents with high wealth and agents with low wealth, and what strategies will survive.

## HOW IT WORKS

X number of agents will be created, X being determined by a slider called number_of_agents. Each agent will be given randomly a strategy when it is the initiator, where he decides how much to give; and as the responder, where he decides at which level being offered, he will reject the offer. The former is in a turtle-own vairable called offer% and the latter rejection%.

Initially, both offer% and rejection% are seeded by a random number between 0 and 99 inclusive by the code random 100.

There is a third turtle-own variable called "wealth". If the offer% by a turtle is accepted, the "wealth" is updated with "wealth" plus (100 - offer%), and the responder's "wealth" is updated with "wealth" plus offer% from the initiator. Wealth is initialised to 50 at the start, the reason for this will be made clear in the next paragraph.

Wealth is used up to maintain life of the agent at each round. Arbitrarily, at each round (tick) the base number 50 will be minus from wealth. That number 50 could be increased or decreased depending on the total population of agents and the carrying capacity of the 'world'. If there are X number of agents, and the carrying capacity is Y, the amount deducted at each round is 50 * X / Y, so when X > Y, more than 50 will be deducted each time, and if X < Y, less than 50 will be deducted. The initial value of wealth being seede with 50 is to allow some agents to survive at least the first round.

## HOW TO USE IT

Use the slider to fix the starting population of agents and use the slider "carrying-capacity" to fix the carrying capacity. Then press go and watch the population chart, the mean wealth chart, the mean offer% and mean rejection%

## THINGS TO NOTICE

If you let the model run, initialising the number of agents to a number less than the carrying capacity, there will be an initial dip in the population number, then rise and reach an equilibrium. The mean wealth will also rise and reach an equilibrium. THe mean offer% might drop a bit and the mean rejection% will drop. The numbers are roughly in line with field findings. When the model has reached an equilibrium if you lower the carrying capacity, the population will drop and so will the rejection% number drops. Does this mean the agents have evolved to be more hungry and willing to accept even low offer? Now increase the carrying capacity to a very big number, you will notice that the rejection% number will rise, and of course so will the population number rise. Does that mean when good times are here, the agents have evolved to be more picky?

## THINGS TO TRY

Try playing around with the population number and the carrying capacity and notice the effect on the offer% and rejection% numbers.

At the moment, the newly hatched agents have their offer% and rejection% modified by random 100, inheriting 50% of the parent's value plus 50% of the random value. Try observe the effect of changing the ratio of inherited value to random value.

## EXTENDING THE MODEL

Have a population of agents where the offer% and refuse% are the same and see what happens.

## NETLOGO FEATURES

The change in the mean offer% and rejection% as a result of the changing carrying capacity to actual population numbers is an emergent phenomenon

## RELATED MODELS
Scalco, A., Ceshi, A., Sartori, R., and Rubaltelli, E. :Exploring Selfish versus Altruistic Behaviors in Ultimatum Game with an Agent-Based Model. Trends in Pracical Application of Agents, Multi-Agent Systems and Sustainability. The PAAM Collection (Vol. 372, pp 1990206): Springer International Publishing.

## CREDITS AND REFERENCES

Güth, W., Schmittberger, R., Schwarze, B.: An experimental analysis of ultimatum bargaining. J. Econ. Behav. Organ. 3, 367-388 (1982)
Oosterbeek, H., Sloof, R., van de Kuilen, G. : Cultural Differences in Ultimatum Game Experiments: Evidence from a Meta-Analysis. Experimental Economics , 7: 171-188, June 2004.
Henrich J. : Does Culture Matter in Economic Behavior? Ultimatum Game Bargaining Among the Machiguenga of the Peruvian Amazon. The American Economic Review Vol. 973-979. 2000

Program written by Ronald Paul Ng.
e-mail: ronaldpaul.ng@gmail.com
Address: ICON, 3 Mt. Elizabeth #17-03/04, Singapore 228510