activity
20192025
most citedAutomated Reinforcement Learning (AutoRL): A Survey and Open Problems

91 citations · 301 across the 27 of their papers we have counts for

collaborators

29 papers

cs.AI2025

Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network

Theresa Eimer, Lennart Schäpermeier, André Biedenkapp +15

Empirical research on meta-algorithmics, such as algorithm selection, configuration, and scheduling, often relies on extensive and thus computationally expensive experiments. With…

cs.LG2025

Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+(,))-GA

Tai Nguyen, Phong Le, André Biedenkapp +2

Dynamic Algorithm Configuration (DAC) studies the efficient identification of control policies for parameterized optimization algorithms. Numerous studies leverage Reinforcement Le…

cs.LG2025

A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam

Rean Fernandes, André Biedenkapp, Frank Hutter +1

Legal reasoning tasks present unique challenges for large language models (LLMs) due to the complexity of domain-specific knowledge and reasoning processes. This paper investigates…

cs.LG2025★ 2 cited

On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(,))-GA

Tai Nguyen, Phong Le, André Biedenkapp +2

Dynamic Algorithm Configuration (DAC) has garnered significant attention in recent years, particularly in the prevalence of machine learning and deep learning algorithms. Numerous…

cs.LG2024

One-shot World Models Using a Transformer Trained on a Synthetic Prior

Fabio Ferreira, Moreno Schlageter, Raghu Rajan +2

A World Model is a compressed spatial and temporal representation of a real world environment that allows one to train an agent or execute planning methods. However, world models a…

cs.LG2024

CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC

Philipp Bordne, M. Asif Hasan, Eddie Bergman +2

High-dimensional action spaces remain a challenge for dynamic algorithm configuration (DAC). Interdependencies and varying importance between action dimensions are further known ke…