Papers Evolutionary Algorithms
“Evolutionary Algorithms” 태그가 달린 논문 1,107편 · 필터 해제
A First Running Time Analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2)
Evolutionary algorithms (EAs) have emerged as a predominant approach for addressing multi-objective optimization problems. However, the theoretical foundation of multi-objective EAs (MOEAs), particularly the fundamental …
2kEvolutionary AlgorithmsEffective Adaptive Mutation Rates for Program Synthesis
The problem-solving performance of many evolutionary algorithms, including genetic programming systems used for program synthesis, depends on the values of hyperparameters including mutation rates. The mutation method us…
Evolutionary AlgorithmsProgram SynthesisSymbolic RegressionEfficient Evolutionary Search Over Chemical Space with Large Language Models
Molecular discovery, when formulated as an optimization problem, presents significant computational challenges because optimization objectives can be non-differentiable. Evolutionary Algorithms (EAs), often used to optim…
Drug DesignEvolutionary AlgorithmsEvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
The rise of powerful large language models (LLMs) has spurred a new trend in building LLM-based autonomous agents for solving complex tasks, especially multi-agent systems. Despite the remarkable progress, we notice that…
Evolutionary AlgorithmsLearning to Transfer for Evolutionary Multitasking
Evolutionary multitasking (EMT) is an emerging approach for solving multitask optimization problems (MTOPs) and has garnered considerable research interest. The implicit EMT is a significant research branch that utilizes…
Evolutionary AlgorithmsTransfer LearningArchive-based Single-Objective Evolutionary Algorithms for Submodular Optimization
Constrained submodular optimization problems play a key role in the area of combinatorial optimization as they capture many NP-hard optimization problems. So far, Pareto optimization approaches using multi-objective form…
Combinatorial OptimizationEvolutionary AlgorithmsKnowledge Fusion By Evolving Weights of Language Models
Fine-tuning pre-trained language models, particularly large language models, demands extensive computing resources and can result in varying performance outcomes across different domains and datasets. This paper examines…
DecoderEvolutionary AlgorithmsLarge Language Models as Surrogate Models in Evolutionary Algorithms: A Preliminary Study
Large Language Models (LLMs) have achieved significant progress across various fields and have exhibited strong potential in evolutionary computation, such as generating new solutions and automating algorithm design. Sur…
Evolutionary AlgorithmsInterpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation
This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in procedural content generation. By balancing t…
DiversityEvolutionary AlgorithmsSokobanDetection-Rate-Emphasized Multi-objective Evolutionary Feature Selection for Network Intrusion Detection
Network intrusion detection is one of the most important issues in the field of cyber security, and various machine learning techniques have been applied to build intrusion detection systems. However, since the number of…
Evolutionary Algorithmsfeature selectionIntrusion DetectionNetwork Intrusion DetectionMeta-Learning an Evolvable Developmental Encoding
Representations for black-box optimisation methods (such as evolutionary algorithms) are traditionally constructed using a delicate manual process. This is in contrast to the representation that maps DNAs to phenotypes i…
DiversityEvolutionary AlgorithmsMeta-LearningAutonomous Multi-Objective Optimization Using Large Language Model
Multi-objective optimization problems (MOPs) are ubiquitous in real-world applications, presenting a complex challenge of balancing multiple conflicting objectives. Traditional evolutionary algorithms (EAs), though effec…
Evolutionary AlgorithmsLanguage ModelingLanguage ModellingLarge Language ModelConserving Human Creativity with Evolutionary Generative Algorithms: A Case Study in Music Generation
This study explores the application of evolutionary generative algorithms in music production to preserve and enhance human creativity. By integrating human feedback into Differential Evolution algorithms, we produced si…
Evolutionary AlgorithmsMusic GenerationAccelerating evolutionary exploration through language model-based transfer learning
Gene expression programming is an evolutionary optimization algorithm with the potential to generate interpretable and easily implementable equations for regression problems. Despite knowledge gained from previous optimi…
Evolutionary AlgorithmsLanguage ModelingLanguage Modellingregression+2Toward Artificial Open-Ended Evolution within Lenia using Quality-Diversity
From the formation of snowflakes to the evolution of diverse life forms, emergence is ubiquitous in our universe. In the quest to understand how complexity can arise from simple rules, abstract computational models, such…
DiversityEvolutionary AlgorithmsAn Archive Can Bring Provable Speed-ups in Multi-Objective Evolutionary Algorithms
In the area of multi-objective evolutionary algorithms (MOEAs), there is a trend of using an archive to store non-dominated solutions generated during the search. This is because 1) MOEAs may easily end up with the final…
Evolutionary AlgorithmsMaintaining Diversity Provably Helps in Evolutionary Multimodal Optimization
In the real world, there exist a class of optimization problems that multiple (local) optimal solutions in the solution space correspond to a single point in the objective space. In this paper, we theoretically show that…
DiversityEvolutionary AlgorithmsLearning to Solve Multiresolution Matrix Factorization by Manifold Optimization and Evolutionary Metaheuristics
Multiresolution Matrix Factorization (MMF) is unusual amongst fast matrix factorization algorithms in that it does not make a low rank assumption. This makes MMF especially well suited to modeling certain types of graphs…
Evolutionary AlgorithmsNode ClassificationEvolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments
The problem of finding the optimal placement of emergency exits in an indoor environment to facilitate the rapid and orderly evacuation of crowds is addressed in this work. A cellular-automaton model is used to simulate …
Evolutionary AlgorithmsA First Look at Kolmogorov-Arnold Networks in Surrogate-assisted Evolutionary Algorithms
Surrogate-assisted Evolutionary Algorithm (SAEA) is an essential method for solving expensive expensive problems. Utilizing surrogate models to substitute the optimization function can significantly reduce reliance on th…
Evolutionary AlgorithmsKolmogorov-Arnold Networks