Farsi / Persian
NetLogo User Community Models
## WHAT IS IT?
This model aims to study the effects of cooperating and competing within a society
Based on the Prisoner’s Dilemma or Game Theory, the Prisoner's Dilemma is usually defined between two players and within Game theory which assumes that players act rationally. Realistic investigations of collective behaviour, however, require a multi-person model of the game that serves as a mathematical formulation of what is going on within a human society.
Various aspects of multi-person Prisoner's Dilemma have been investigated, but till today there is still no consensus about its real meaning.
The multi-person Prisoner's Dilemma considers a situation when each of N participants has a choice between two actions: cooperating with each other for the "common good" or defecting (following their selfish short-term interests). As a result of their choice, each participant receives a reward or punishment (payoff) that is dependent on its choice as well as everybody else's.
## HOW IT WORKS
Each patch will either cooperate (blue) or compete (red) at the start of the model
Each patch will receive a score based on its own choice and the choice its immediate (8) neighbours have chosen
In the next round, each patch will be assigned a strategy and behave accordingly based on the previous round
Strategies are assigned to each agent based on their choice of action and the respective score it received from it. Agents who do well while cooperating will continue to cooperate, while agents who do poorly while cooperating will change their strategy, and agents who do fairly average while cooperating will employ a tit-for-tat strategy. Similarly, agents who do well while competing will continue to compete, while agents who do poorly while competing will change their strategy, and agents who do fairly average will employ the tit-for-tat strategy.
## HOW TO USE IT
## THINGS TO NOTICE
Notice the strategies used during the simulation and compare it to the end result. How has the use of each strategy changed over time.
Are the payoff curves the same for all agents? How do they differ?
How is the total payoff to all agents related to the number of cooperators?
Notice when do agents who compete score highest and when do they score similar to those who cooperate.
## THINGS TO TRY
Try sliding the initial-cooperation slider to configure the starting number of cooperators. How does it affect the score of the agents. How does it affect the strategies employed by agents?
## EXTENDING THE MODEL
Derive and use a proper formula instead of using logic to assign strategies to the agents.
Incorporate space into the model and allow patches to move about and interact with different patches. This allows patches to form coalitions and also the ability to choose to participate in a round of interaction or not. Doing so enables the user to increase the number of strategies available to choose from as well.
Extend the model so that each agent interacts with everyone else instead of simply interacting with its immediate neighbours. As the sample increases, how does this affect the result?
## RELATED MODELS
PD N-Person Iterated
PD Basic Evolutionary
## CREDITS AND REFERENCES
Miklos N. Szilagyi. An Investigation of N-person Prisoners' Dilemmas. Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, 85721. http://www.complex-systems.com/pdf/14-2-3.pdf
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