Arkadiy Dushatskiy,Marco Virgolin,Anton Bouter et al.
Arkadiy Dushatskiy et al.
When it comes to solving optimization problems with evolutionary algorithms (EAs) in a reliable and scalable manner, detecting and exploiting linkage information, i.e., dependencies between variables, can be key. In this article, we present...
The Role of Morphological Variation in Evolutionary Robotics: Maximizing Performance and Robustness [0.03%]
形态变异在进化机器人学中的作用：最大化性能和鲁棒性
Jonata Tyska Carvalho,Stefano Nolfi
Jonata Tyska Carvalho
Exposing an evolutionary algorithm that is used to evolve robot controllers to variable conditions is necessary to obtain solutions which are robust and can cross the reality gap. However, we do not yet have methods for analyzing and unders...
Territorial Differential Meta-Evolution: An Algorithm for Seeking All the Desirable Optima of a Multivariable Function [0.03%]
区域差异元进化：一种用于求解多变量函数全优解的算法
Richard Wehr,Scott R Saleska
Richard Wehr
Territorial Differential Meta-Evolution (TDME) is an efficient, versatile, and reliable algorithm for seeking all the global or desirable local optima of a multivariable function. It employs a progressive niching mechanism to optimize even ...
Thomas H W Bäck,Anna V Kononova,Bas van Stein et al.
Thomas H W Bäck et al.
Thirty years, 1993-2023, is a huge time frame in science. We address some major developments in the field of evolutionary algorithms, with applications in parameter optimization, over these 30 years. These include the covariance matrix adap...
Nikolaus Frohner,Bernhard Neumann,Giulio Pace et al.
Nikolaus Frohner et al.
The traveling tournament problem is a well-known sports league scheduling problem famous for its practical hardness. Given an even number of teams with symmetric distances between their venues, a double round-robin tournament has to be sche...
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem [0.03%]
求解双目标最小生成树问题的单目标子图基变异方法
Jakob Bossek,Christian Grimme
Jakob Bossek
We contribute to the efficient approximation of the Pareto-set for the classical NP-hard multiobjective minimum spanning tree problem (moMST) adopting evolutionary computation. More precisely, by building upon preliminary work, we analyze t...
Comparing Robot Controller Optimization Methods on Evolvable Morphologies [0.03%]
比较可进化形态机器人控制器的优化方法
Fuda van Diggelen,Eliseo Ferrante,A E Eiben
Fuda van Diggelen
In this paper, we compare Bayesian Optimization, Differential Evolution, and an Evolution Strategy employed as a gait-learning algorithm in modular robots. The motivational scenario is the joint evolution of morphologies and controllers, wh...
Comparative Study
Evolutionary computation. 2024 Jun 3;32(2):105-124. DOI:10.1162/evco_a_00334 2024
The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond [0.03%]
约束的重要性：处理差分进化及其他方法中的不可行解问题
Anna V Kononova,Diederick Vermetten,Fabio Caraffini et al.
Anna V Kononova et al.
We argue that results produced by a heuristic optimisation algorithm cannot be considered reproducible unless the algorithm fully specifies what should be done with solutions generated outside the domain, even in the case of simple bound co...
A Data Stream Ensemble Assisted Multifactorial Evolutionary Algorithm for Offline Data-Driven Dynamic Optimization [0.03%]
一种用于离线数据驱动动态优化的多因素进化算法及其流数据增强方法
Cuie Yang,Jinliang Ding,Yaochu Jin et al.
Cuie Yang et al.
Existing work on offline data-driven optimization mainly focuses on problems in static environments, and little attention has been paid to problems in dynamic environments. Offline data-driven optimization in dynamic environments is a chall...
Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy [0.03%]
基于协方差矩阵自适应进化策略的神经网络结构搜索方法
Nilotpal Sinha,Kuan-Wen Chen
Nilotpal Sinha
Evolution-based neural architecture search methods have shown promising results, but they require high computational resources because these methods involve training each candidate architecture from scratch and then evaluating its fitness, ...