6 citations · 9 across the 4 of their papers we have counts for
13 papers
Population Diversity Leads to Short Running Times of Lexicase Selection
Thomas Helmuth, Johannes Lengler, William La Cava
In this paper we investigate why the running time of lexicase parent selection is empirically much lower than its worst-case bound of O(N*C). We define a measure of population dive…
Large Population Sizes and Crossover Help in Dynamic Environments
Johannes Lengler, Jonas Meier
Dynamic linear functions on the hypercube are functions which assign to each bit a positive weight, but the weights change over time. Throughout optimization, these functions maint…
Stopping explosion by penalising transmission to hubs in scale-free spatial random graphs
Júlia Komjáthy, John Lapinskas, Johannes Lengler
We study the spread of information in finite and infinite inhomogeneous spatial random graphs. We assume that each edge has a transmission cost that is a product of an i.i.d. rando…
Exponential Slowdown for Larger Populations: The -EA on Monotone Functions
Johannes Lengler, Xun Zou
Pseudo-Boolean monotone functions are unimodal functions which are trivial to optimize for some hillclimbers, but are challenging for a surprising number of evolutionary algorithms…
The linear hidden subset problem for the (1+1) EA with scheduled and adaptive mutation rates
Hafsteinn Einarsson, Marcelo Matheus Gauy, Johannes Lengler +4
We study unbiased evolutionary algorithms on linear functions with an unknown number of bits with non-zero weight. Static algorithms achieve an optimal runtime of $O(n…
When Does Hillclimbing Fail on Monotone Functions: An entropy compression argument
Johannes Lengler, Anders Martinsson, Angelika Steger
Hillclimbing is an essential part of any optimization algorithm. An important benchmark for hillclimbing algorithms on pseudo-Boolean functions are (s…