EvoLudoLab: Rock-Paper-Scissors - ODE: Difference between revisions
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{{EvoLudoLab:RSP| | {{EvoLudoLab:RSP| | ||
options="-- | options="--game RSP --model ODE --run --delay 50 --view Strategies_-_Simplex_S3 --reportfreq 0.1 --playerupdate imitate --playerupdatenoise 1 --init 20,20,60 --inittype frequencies --mutation 0.0 --basefit 1.0 --selection 1.0 --paymatrix 0,0.7,-1;-1,0,3.4;0.8,-1,0"| | ||
title=Replicator dynamics| | title=Replicator dynamics| | ||
doc= | doc=For \(s>1\) the interior fixed point \(\hat x\) is a stable focus of the replicator dynamics. All trajectories spiral toward \(\hat x\). | ||
The parameters are | The parameters are \(s = 1.4\) using numerical integration of the replicator equation (Runge-Kutta with variable step size). | ||
''Tip:'' Use the context menu to switch between forward and backward integration in time. | ''Tip:'' Use the context menu to switch between forward and backward integration in time. | ||
}} |
Latest revision as of 15:49, 12 October 2023
Color code: | Rock | Scissors | Paper |
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New rock | New scissors | New paper |
Payoffs: | Low High
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Note: The gradient of the payoff scale is augmented by pale shades of the strategy colours to mark payoffs that are achieved in homogeneous populations of the corresponding type.
Replicator dynamics
For \(s>1\) the interior fixed point \(\hat x\) is a stable focus of the replicator dynamics. All trajectories spiral toward \(\hat x\).
The parameters are \(s = 1.4\) using numerical integration of the replicator equation (Runge-Kutta with variable step size).
Tip: Use the context menu to switch between forward and backward integration in time.
Data views
Snapshot of the spatial arrangement of strategies. | |
Snapshot of the spatial arrangement of strategies in 3D. | |
Time evolution of the strategy frequencies. | |
Trajectories of strategy frequencies shown in the simplex \(S_3\). Double clicks in the interior of \(S_3\) set the initial frequencies of strategies. | |
Snapshot of the spatial distribution of payoffs. | |
Snapshot of the spatial distribution of payoffs in 3D. | |
Time evolution of average population payoff bounded by the minimum and maximum individual payoff. | |
Payoff distribution of each strategy in population. | |
Degree distribution in structured populations. | |
Displays messages, warnings and errors reported by the simulation engine plus information on the applet/application. |
Game parameters
The list below describes only the parameters related to the rock-scissors-paper game and the population dynamics. Follow the link for a complete list and descriptions of all other parameters such as spatial arrangements or update rules on the player and population level.
- --paymatrix <rr,rs,rp;sr,ss,sp;pr,ps,pp>
- general \(3\times 3\) payoff matrix for the three strategic types \(R, S, P\).
- --init <r,s,p>
- initial frequencies of \(R, S, P\), respectively. Frequencies that do not add up to 100% are scaled accordingly.
- --inittype <type>
- type of initial configuration:
- frequency
- random distribution with given frequency
- uniform
- uniform random distribution
- monomorphic
- monomorphic initialization
- mutant
- single mutant in homogeneous population of another type. Mutant and resident types are determined by the types with the lowest and highest frequency, respectively (see option --init).
- stripes
- stripes of traits
- kaleidoscopes
- (optional) configurations that produce evolutionary kaleidoscopes for deterministic updates (players and population). Not available for all types of games.