IEEE

Automated Configuration of Evolutionary Algorithms via Deep Reinforcement Learning for Constrained Multiobjective Optimization

Abstract: Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms ...

Social media’s next evolution: user-controlled algorithms

Social media feeds are becoming more customizable as platforms like Threads, Instagram, and TikTok introduce tools that let users directly influence the algorithms powering their recommendations.
IEEE

EMT-DAKT: Evolutionary Multi-Objective Multi-Task Optimization Algorithm Using Deep Models With Adaptive Knowledge Transfer

Abstract: Evolutionary multi-objective multi-task optimization (MO-MTO) can optimize multiple tasks simultaneously by knowledge transfer (KT) between tasks. However, the existing MO-MTO algorithms ...