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All Mutation Rates $c/n$ for the $(1+1)$ Evolutionary Algorithm

Andrew James Kelley

TL;DR

The set of all $c \geq 1$ for which the mutation rate $c/n$ is optimal for the $(1+1)$ EA is dense in the interval $[1, \infty)$.

Abstract

For every real number $c \geq 1$ and for all $\varepsilon > 0$, there is a fitness function $f : \{0,1\}^n \to \mathbb{R}$ for which the optimal mutation rate for the $(1+1)$ evolutionary algorithm on $f$, denoted $p_n$, satisfies $p_n \approx c/n$ in that $|np_n - c| < \varepsilon$. In other words, the set of all $c \geq 1$ for which the mutation rate $c/n$ is optimal for the $(1+1)$ EA is dense in the interval $[1, \infty)$. To show this, a fitness function is introduced which is called HillPathJump.

All Mutation Rates $c/n$ for the $(1+1)$ Evolutionary Algorithm

TL;DR

The set of all for which the mutation rate is optimal for the EA is dense in the interval .

Abstract

For every real number and for all , there is a fitness function for which the optimal mutation rate for the evolutionary algorithm on , denoted , satisfies in that . In other words, the set of all for which the mutation rate is optimal for the EA is dense in the interval . To show this, a fitness function is introduced which is called HillPathJump.
Paper Structure (4 sections, 11 theorems, 13 equations, 1 table)

This paper contains 4 sections, 11 theorems, 13 equations, 1 table.

Key Result

Lemma 1

Let $x^+$ be the individual with second highest fitness. Then the hamming distance between $x^+$ and $x^*$, denoted $H(x^+, x^*)$, is $k$.

Theorems & Definitions (21)

  • Lemma 1
  • proof
  • Theorem 2
  • Theorem 3
  • Lemma 4
  • proof
  • Lemma 5
  • proof
  • Lemma 6
  • proof
  • ...and 11 more