10 papers · 1 filter
Learning to Prompt: Improving Student Engagement with Adaptive LLM-based High-School Tutoring
Po-Chin Chang, Nicholas Hogan, Aske Plaat +1
LLMs can personalize education, although current static-prompt tutoring systems struggle to adapt to diverse academic disciplines. We develop and test a system with subject-aware p…
Mirror Mode in Fire Emblem: Beating Players at their own Game with Imitation and Reinforcement Learning
Yanna Elizabeth Smid, Peter van der Putten, Aske Plaat
Enemy strategies in turn-based games should be surprising and unpredictable. This study introduces Mirror Mode, a new game mode where the enemy AI mimics the personal strategy of a…
Agentic Large Language Models, a survey
Aske Plaat, Max van Duijn, Niki van Stein +3
Background: There is great interest in agentic LLMs, large language models that act as agents. Objectives: We review the growing body of work in this area and provide a research ag…
Multi-Step Reasoning with Large Language Models, a Survey
Aske Plaat, Annie Wong, Suzan Verberne +3
Large language models (LLMs) with billions of parameters exhibit in-context learning abilities, enabling few-shot learning on tasks that the model was not specifically trained for.…
Guiding Skill Discovery with Foundation Models
Zhao Yang, Thomas M. Moerland, Mike Preuss +3
Learning diverse skills without hand-crafted reward functions could accelerate reinforcement learning in downstream tasks. However, existing skill discovery methods focus solely on…
A Benchmark Study of Deep Reinforcement Learning Algorithms for the Container Stowage Planning Problem
Yunqi Huang, Nishith Chennakeshava, Alexis Carras +4
Container stowage planning (CSPP) is a critical component of maritime transportation and terminal operations, directly affecting supply chain efficiency. Owing to its complexity, C…