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Evolutionary Stability One Mutant Payoff Gap Tool

Check the two ESS inequalities against one specified mutant, not against all possible mutant strategies.

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Description

Return residentResident-minus-mutantResident and residentMutant-minus-mutantMutant.

Game-theoretic payoffs describe a chosen model of actions and incentives. A deviation, discounted term or local payoff contribution is only one part of the relevant equilibrium or welfare conditions.

Return residentResident-minus-mutantResident and residentMutant-minus-mutantMutant.

When to use this tool

Use Evolutionary Stability One Mutant Payoff Gap when you need one transparent payoff or incentive comparison.

How to use the tool and how it works

  1. Enter residentResident, mutantResident, residentMutant, mutantMutant. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read primaryGap, secondaryGap, satisfiesPairCondition. Inspect satisfiesPairCondition before interpreting the associated values.

Return residentResident-minus-mutantResident and residentMutant-minus-mutantMutant. Pass the pair condition when the first gap is positive, or exactly zero with the second positive.1

Input fieldMeaning and unitsAccepted input
residentResidentResident ResidentRequired. Finite number.
mutantResidentMutant ResidentRequired. Finite number.
residentMutantResident MutantRequired. Finite number.
mutantMutantMutant MutantRequired. Finite number.
Output fieldInterpretationReturned shape
primaryGapPrimary GapRequired. Finite number.
secondaryGapSecondary GapRequired. Finite number.
satisfiesPairConditionSatisfies Pair ConditionRequired. Boolean.
json
{
  "input": {
    "residentResident": 3,
    "mutantResident": 3,
    "residentMutant": 2,
    "mutantMutant": 1
  },
  "output": {
    "primaryGap": 0,
    "secondaryGap": 1,
    "satisfiesPairCondition": true
  }
}

Limitations and assumptions

  • This tests one resident/mutant pair under the two-condition evolutionary-stability comparison, not all possible mutants or population dynamics.
  • 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

Evaluate the complete strategy space, timing and payoff model for an equilibrium claim. Test robustness to assumptions rather than treating a local incentive inequality as a prediction of actual behavior.

References

  1. Calculation and input contract: game-theory/evolutionary-stability-one-mutant-payoff-gap — tool.io

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