63 citations · 151 across the 18 of their papers we have counts for
8 papers · 1 filter
Integer Natural Evolution Strategies
Jacob de Nobel, Diederick Vermetten, Hao Wang +3
While contemporary Evolution Strategies handle integer optimization problems effectively, their adaptation mechanism is grounded in -based Gaussian models, which are not na…
Avoiding Redundant Restarts in Multimodal Global Optimization
Jacob de Nobel, Diederick Vermetten, Anna V. Kononova +2
Naïve restarts of global optimization solvers when operating on multimodal search landscapes may resemble the Coupon's Collector Problem, with a potential to waste significant func…
Multi-Level Evolution Strategies for High-Resolution Black-Box Control
Ofer M. Shir, Xi Xing, Herschel Rabitz
This paper introduces a multi-level (m-lev) mechanism into Evolution Strategies (ESs) in order to address a class of global optimization problems that could benefit from fine discr…
Benchmarking Discrete Optimization Heuristics with IOHprofiler
Carola Doerr, Furong Ye, Naama Horesh +3
Automated benchmarking environments aim to support researchers in understanding how different algorithms perform on different types of optimization problems. Such comparisons provi…
On the Covariance-Hessian Relation in Evolution Strategies
Ofer M. Shir, Amir Yehudayoff
We consider Evolution Strategies operating only with isotropic Gaussian mutations on positive quadratic objective functions, and investigate the covariance matrix when constructed…
On the Theoretical Capacity of Evolution Strategies to Statistically Learn the Landscape Hessian
Ofer M. Shir, Jonathan Roslund, Amir Yehudayoff
We study the theoretical capacity to statistically learn local landscape information by Evolution Strategies (ESs). Specifically, we investigate the covariance matrix when construc…
Quantum Control Experiments as a Testbed for Evolutionary Multi-Objective Algorithms
Ofer M. Shir, Jonathan Roslund, Zaki Leghtas +1
Experimental multi-objective Quantum Control is an emerging topic within the broad physics and chemistry applications domain of controlling quantum phenomena. This realm offers cut…
Evolutionary Hessian Learning: Forced Optimal Covariance Adaptive Learning (FOCAL)
Ofer M. Shir, Jonathan Roslund, Darrell Whitley +1
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) has been the most successful Evolution Strategy at exploiting covariance information; it uses a form of Principle Compo…