EvoLudoLab: Continuous Snowdrift Game - Defection
Along the bottom of the applet there are several buttons to control the execution and the speed of the simulations - for details see the EvoLudo GUI documentation. Of particular importance are the parameters button and the data data views pop-up list along the top. The former opens a panel that allows to set and change various parameters concerning the game as well as the population structure, while the latter displays the simulation data in different ways.
Color code: | Maximum | Minimum | Mean |
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Strategy code: | Defect | Cooperate |
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Payoff code: | Low | High |
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Note: The shades of grey of the payoff scale are augmented by blueish and reddish shades indicating payoffs for mutual cooperation and defection, respectively.
Continuous Snowdrift game: Dilemma
This situation corresponds to the continuous Prisoner's Dilemma, where lower investing individuals always outperform higher investors. Therefore investment levels decrease and cooperation vanishes.
The parameters are set to \(b_2 = -1.5, b_1 = 7, c_2 = -1, c_1 = 8\) with players imitating better strategies proportional to the payoff difference and an initial traits/investment of \(0.9 \pm 0.02\) in a population of \(5'000\) individuals. Mutations occur with a probability of 1% and the standard deviation of the Gaussian distributed mutations is \(0.01\).
Data views | |
Snapshot of the spatial arrangement of strategies. | |
Time evolution of the strategy frequencies. | |
Snapshot of strategy distribution in population | |
Time evolution of the strategy distribution | |
Snapshot of the spatial distribution of payoffs. | |
Time evolution of average population payoff bounded by the minimum and maximum individual payoff. | |
Snapshot of payoff distribution in population. | |
Degree distribution in structured populations. | |
Message log from engine. |
Game parameters
The list below describes only the few parameters related to the continuous snowdrift game. Follow the link for a complete list and descriptions of all other parameters e.g. referring to update mechanisms of players and the population.
- Benefit/Cost Functions
- A variety of different combinations of cost and benefit functions can be selected.
- Benefit \(b_0,\ b_1\)
- Two parameters for the benefit function. Note that not all functions require both.
- Cost \(c_0,\ c_1\)
- Two parameters for the cost function. Note that not all functions require both.
- Mean invest
- Mean trait value of initial population.
- Sdev invest
- Standard deviation of initial population. If set to negative values, the population will be initialized with uniform distributed traits.