Nature

Computer science articles from across Nature Portfolio

Large language models appear aligned, yet harmful pretraining knowledge persists as latent patterns. Here, the authors prove current alignment creates only local safety regions, leaving global ...
IEEE

Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms

Abstract: Evolutionary reinforcement learning (ERL), which integrates the evolutionary algorithms (EAs) and reinforcement learning (RL) for optimization, has demonstrated remarkable performance ...
IEEE

Deep Reinforcement Learning for Smart Grid Operations: Algorithms, Applications, and Prospects

Abstract: With the increasing penetration of renewable energy and flexible loads in smart grids, a more complicated power system with high uncertainty is gradually formed, which brings about great ...
GitHub

LLM4AD: Large Language Model for Algorithm Design

LLM4AD is an open-source Python-based Platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). Please refer to the paper [LLM4AD] for detailed information, including the ...
www.cs.utexas.edu

Efficient Evolution of Neural Networks Through Complexification (2004)

Artificial neural networks can potentially control autonomous robots, vehicles, factories, or game players more robustly than traditional approaches. Neuroevolution, i.e. the artificial evolution of ...