Description
Dot payoffs with frequencies and add scaled payoff to baseline fitness.
Population-genetic fitness models use explicit allele frequencies, genotype fitnesses and generation rules. Relative fitness and a selection coefficient require a sign convention, and a deterministic update describes a model rather than an observed population trajectory.
Dot payoffs with frequencies and add scaled payoff to baseline fitness.
When to use this tool
Use Evolutionary Game Fitness One Strategy Term when you need a supplied one-step fitness or allele-frequency relationship.
How to use the tool and how it works
- Enter payoffs, opponentFrequencies, baselineFitness, selectionIntensity. Keep parallel arrays aligned. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read expectedPayoff, fitness. Use the output convention below.
Require aligned nonempty payoff/frequency arrays, nonnegative frequencies totaling within 1e-12 of one and nonnegative resulting fitness. Dot payoffs with frequencies and add scaled payoff to baseline fitness.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| payoffs | Payoffs | Required. Array of finite number; maximum items 256. |
| opponentFrequencies | Opponent Frequencies | Required. Array of finite number; maximum items 256. |
| baselineFitness | Baseline Fitness | Required. Finite number. |
| selectionIntensity | Selection Intensity | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| expectedPayoff | Expected Payoff | Required. Finite number. |
| fitness | Fitness | Required. Finite number. |
{
"input": {
"payoffs": [
4,
1
],
"opponentFrequencies": [
0.25,
0.75
],
"baselineFitness": 1,
"selectionIntensity": 0.5
},
"output": {
"expectedPayoff": 1.75,
"fitness": 1.875
}
}Limitations and assumptions
- Frequencies are not renormalized. This is one strategy's supplied linear fitness map, not an equilibrium, selection-intensity estimate or population trajectory.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Use a population model appropriate to mating, selection, mutation, migration and drift. Estimate parameters and uncertainty from suitable data instead of treating a supplied model step as a prediction.
References
Similar or alternative tools
- Evolutionary Stability One Mutant Payoff Gap
Return residentResident-minus-mutantResident and residentMutant-minus-mutantMutant.
- Selection Reference Fitness Sign
Return relative fitness and one minus that ratio as selectionCoefficient.