Language model crossover: Variation through few-shot prompting
This article pursues the insight that language models naturally enable an intelligent variation
operator similar in spirit to evolutionary crossover. In particular, language models of …
operator similar in spirit to evolutionary crossover. In particular, language models of …
Using a variational autoencoder to learn valid search spaces of safely monitored autonomous robots for last-mile delivery
The use of autonomous robots for delivery of goods to customers is an exciting new way to
provide a reliable and sustainable service. However, in the real world, autonomous robots …
provide a reliable and sustainable service. However, in the real world, autonomous robots …
Dual-drive collaboration surrogate-assisted evolutionary algorithm by coupling feature reduction and reconstruction
H Yu, Y Gong, L Kang, C Sun, J Zeng - Complex & Intelligent Systems, 2024 - Springer
Surrogate-assisted evolutionary algorithm (SAEA) prevails in the optimization of
computationally expensive problems. However, existing SAEAs confront low efficiency in the …
computationally expensive problems. However, existing SAEAs confront low efficiency in the …
COIL: Constrained optimization in learned latent space: Learning representations for valid solutions
Constrained optimization problems can be difficult because their search spaces have
properties not conducive to search, eg, multimodality, discontinuities, or deception. To …
properties not conducive to search, eg, multimodality, discontinuities, or deception. To …
Dynamic Chromosome Interpretation in Evolutionary Algorithms for Distributed Energy Resources Scheduling
R Poppenborg, K Phipps, H Khalloof… - Proceedings of the …, 2023 - dl.acm.org
Integrating renewable generation into the existing electricity grid to reduce Greenhouse Gas
(GHG) emissions involves several challenges. These include, eg, volatile generation and …
(GHG) emissions involves several challenges. These include, eg, volatile generation and …
Heuristically Adaptive Diffusion-Model Evolutionary Strategy
Diffusion Models represent a significant advancement in generative modeling, employing a
dual-phase process that first degrades domain-specific information via Gaussian noise and …
dual-phase process that first degrades domain-specific information via Gaussian noise and …
Introduction to Algogens
A Shachar - arXiv preprint arXiv:2403.01426, 2024 - arxiv.org
This book introduces the concept of Algogens, a promising integration of generative AI with
traditional algorithms aimed at improving problem-solving techniques across various fields …
traditional algorithms aimed at improving problem-solving techniques across various fields …
Dynamic Phenotype Mapping in Evolutionary Algorithms for Energy Hub Scheduling
R Poppenborg, K Phipps, M Beichter… - Energy Informatics …, 2024 - Springer
Abstract The integration of Renewable Energy Resources into the existing electricity grid to
reduce Greenhouse Gas emissions raises several challenges, such as volatile generation …
reduce Greenhouse Gas emissions raises several challenges, such as volatile generation …
On 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 …
on their performance. Examination of the suitability of widely used representations for quality …
The Adaptive Search Strategy Selection Based on the Guide of Two Learning Mechanisms for High-Dimensional Expensive Problems
Y Gong, L Kang, G Qiao, D Guo, H Yu… - 2023 5th International …, 2023 - ieeexplore.ieee.org
To enhance the efficiency of the surrogate-assisted evolutionary algorithm (SAEA) for
solving high-dimensional expensive optimization problems with multiple local optima and …
solving high-dimensional expensive optimization problems with multiple local optima and …