Papers Evolutionary Algorithms
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Initial Steps Towards Tackling High-dimensional Surrogate Modeling for Neuroevolution Using Kriging Partial Least Squares
Surrogate-assisted evolutionary algorithms (SAEAs) aim to use efficient computational models with the goal of approximating the fitness function in evolutionary computation systems. This area of research has been active …
Evolutionary AlgorithmsA Line Complex-Based Evolutionary Algorithm for Many-Objective Optimization
Abstract—In solving many-objective optimization problems (MaOPs), existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection pres- sure. Most candidate solutions…
Evolutionary AlgorithmsPositionDiffusion Probabilistic Model Based Accurate and High-Degree-of-Freedom Metasurface Inverse Design
Conventional meta-atom designs rely heavily on researchers' prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient processes. Inverse design methods based on…
Evolutionary AlgorithmsHow Well Does the Metropolis Algorithm Cope With Local Optima?
The Metropolis algorithm (MA) is a classic stochastic local search heuristic. It avoids getting stuck in local optima by occasionally accepting inferior solutions. To better and in a rigorous manner understand this abili…
Evolutionary AlgorithmsHow the Move Acceptance Hyper-Heuristic Copes With Local Optima: Drastic Differences Between Jumps and Cliffs
In recent work, Lissovoi, Oliveto, and Warwicker (Artificial Intelligence (2023)) proved that the Move Acceptance Hyper-Heuristic (MAHH) leaves the local optimum of the multimodal cliff benchmark with remarkable efficien…
Evolutionary AlgorithmsOpen-Ended Question AnsweringControllable Neural Symbolic Regression
In symbolic regression, the goal is to find an analytical expression that accurately fits experimental data with the minimal use of mathematical symbols such as operators, variables, and constants. However, the combinato…
Evolutionary AlgorithmsregressionSymbolic RegressionDECN: Evolution Inspired Deep Convolution Network for Black-box Optimization
Evolutionary algorithms (EAs) have emerged as a powerful framework for optimization, especially for black-box optimization. Existing evolutionary algorithms struggle to comprehend and effectively utilize task-specific in…
Evolutionary AlgorithmsMeta-LearningRank-Based Learning and Local Model Based Evolutionary Algorithm for High-Dimensional Expensive Multi-Objective Problems
Surrogate-assisted evolutionary algorithms have been widely developed to solve complex and computationally expensive multi-objective optimization problems in recent years. However, when dealing with high-dimensional opti…
Evolutionary AlgorithmsComma Selection Outperforms Plus Selection on OneMax with Randomly Planted Optima
It is an ongoing debate whether and how comma selection in evolutionary algorithms helps to escape local optima. We propose a new benchmark function to investigate the benefits of comma selection: OneMax with randomly pl…
Evolutionary AlgorithmsAnalysing Equilibrium States for Population Diversity
Population diversity is crucial in evolutionary algorithms as it helps with global exploration and facilitates the use of crossover. Despite many runtime analyses showing advantages of population diversity, we have no cl…
DiversityEvolutionary AlgorithmsEvolving Constrained Reinforcement Learning Policy
Evolutionary algorithms have been used to evolve a population of actors to generate diverse experiences for training reinforcement learning agents, which helps to tackle the temporal credit assignment problem and improve…
Evolutionary Algorithmsreinforcement-learningReinforcement LearningSelf Optimisation and Automatic Code Generation by Evolutionary Algorithms in PLC based Controlling Processes
The digital transformation of automation places new demands on data acquisition and processing in industrial processes. Logical relationships between acquired data and cyclic process sequences must be correctly interpret…
Code GenerationEvolutionary AlgorithmsEfficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Search
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectures. This rise is mainly due to the popul…
Evolutionary AlgorithmsNeural Architecture SearchExperience-Based Evolutionary Algorithms for Expensive Optimization
Optimization algorithms are very different from human optimizers. A human being would gain more experiences through problem-solving, which helps her/him in solving a new unseen problem. Yet an optimization algorithm neve…
Evolutionary AlgorithmsMeta-LearningOn the Suitability of Representations for Quality Diversity Optimization of Shapes
The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in…
DiversityEvolutionary AlgorithmsIs it conceivable that neurogenesis, neural Darwinism, and species evolution could all serve as inspiration for the creation of evolutionary deep neural networks?
Deep Neural Networks (DNNs) are built using artificial neural networks. They are part of machine learning methods that are capable of learning from data that have been used in a wide range of applications. DNNs are mainl…
AllEvolutionary AlgorithmsDoubly Stochastic Matrix Models for Estimation of Distribution Algorithms
Problems with solutions represented by permutations are very prominent in combinatorial optimization. Thus, in recent decades, a number of evolutionary algorithms have been proposed to solve them, and among them, those b…
Combinatorial OptimizationEvolutionary AlgorithmsInterpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition
Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model that can be insightful to users. Historical…
Bayesian OptimizationEvolutionary AlgorithmsregressionSymbolic RegressionEvolving Artificial Neural Networks To Imitate Human Behaviour In Shinobi III : Return of the Ninja Master
Our society is increasingly fond of computational tools. This phenomenon has greatly increased over the past decade following, among other factors, the emergence of a new Artificial Intelligence paradigm. Specifically, t…
Dynamic neural networksEvolutionary AlgorithmsNeuroevolution of Recurrent Architectures on Control Tasks
Modern artificial intelligence works typically train the parameters of fixed-sized deep neural networks using gradient-based optimization techniques. Simple evolutionary algorithms have recently been shown to also be cap…
Evolutionary AlgorithmsOpenAI Gymreinforcement-learningReinforcement Learning