13 citations · 27 across the 5 of their papers we have counts for
5 papers
The impact of objective interactions on the performance of massive objective optimization algorithms
Shakiba Shahbandegan, Jose Guadalupe Hernandez, Emily Dolson
Many-objective optimization has been a field of interest over the past two decades and several evolutionary optimization algorithms have been introduced to tackle these problems; y…
Phylogeny-informed fitness estimation
Alexander Lalejini, Matthew Andres Moreno, Jose Guadalupe Hernandez +1
Phylogenies (ancestry trees) depict the evolutionary history of an evolving population. In evolutionary computing, a phylogeny can reveal how an evolutionary algorithm steers a pop…
A suite of diagnostic metrics for characterizing selection schemes
Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria
Benchmark suites are crucial for assessing the performance of evolutionary algorithms, but the constituent problems are often too complex to provide clear intuition about an algori…
What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms?
Jose Guadalupe Hernandez, Alexander Lalejini, Emily Dolson
It is generally accepted that "diversity" is associated with success in evolutionary algorithms. However, diversity is a broad concept that can be measured and defined in a multitu…
An Exploration of Exploration: Measuring the ability of lexicase selection to find obscure pathways to optimality
Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria
Parent selection algorithms (selection schemes) steer populations through a problem's search space, often trading off between exploitation and exploration. Understanding how select…