104 citations · 367 across the 54 of their papers we have counts for
5 papers · 1 filter
LLaMEA-SAGE: Guiding Automated Algorithm Design with Structural Feedback from Explainable AI
Niki van Stein, Anna V. Kononova, Lars Kotthoff +1
Large language models have enabled automated algorithm design (AAD) by generating optimization algorithms directly from natural-language prompts. While evolutionary frameworks such…
How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series
Mathieu Cherpitel, Janne Luijten, Thomas Bäck +3
Automated analysis of needle electromyography (nEMG) signals is emerging as a tool to support the detection of neuromuscular diseases (NMDs), yet the signals' high and heterogeneou…
From Performance to Understanding: A Vision for Explainable Automated Algorithm Design
Niki van Stein, Anna V. Kononova, Thomas Bäck
Automated algorithm design is entering a new phase: Large Language Models can now generate full optimisation (meta)heuristics, explore vast design spaces and adapt through iterativ…
Reasoning Capabilities of Large Language Models on Dynamic Tasks
Annie Wong, Thomas Bäck, Aske Plaat +2
Large language models excel on static benchmarks, but their ability as self-learning agents in dynamic environments remains unclear. We evaluate three prompting strategies: self-re…
Graphical Models for Decision-Making: Integrating Causality and Game Theory
Maarten C. Vonk, Mauricio Gonzalez Soto, Anna V. Kononova
Causality and game theory are two influential fields that contribute significantly to decision-making in various domains. Causality defines and models causal relationships in compl…