91 citations · 129 across the 16 of their papers we have counts for
3 papers · 1 filter
Efficient Heteroscedastic Bayesian Optimization for Risk-Aware AutoRL
Mingxuan Che, Tsung-Yuan Tseng, Theresa Eimer +2
Reinforcement learning (RL) has shown remarkable success across a wide range of complex tasks. However, RL outcomes can be highly stochastic, and both expected performance and vari…
Environment-Grounded Automated Prompt Optimization for LLM Game Agents
Rean Clive Fernandes, Lukas Fehring, Theresa Eimer +2
LLM agents in interactive environments are highly sensitive to their prompts, yet prompt engineering remains a manual, task-specific process. We introduce an automated prompt optim…
Learning to Play Blackjack: A Curriculum Learning Perspective
Amirreza Alasti, Efe Erdal, Yücel Celik +1
Reinforcement Learning (RL) agents often struggle with efficiency and performance in complex environments. We propose a novel framework that uses a Large Language Model (LLM) to dy…