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Andreas Persson

2 accepted papers

2025

REvolve: Reward Evolution with Large Language Models using Human Feedback

ICLR 2025poster

Designing effective reward functions is crucial to training reinforcement learning (RL) algorithms. However, this design is non-trivial, even for domain experts, due to the subjective nature of certain tasks that are hard to quantify explicitly. In recent works, large language models (LLMs) have bee…

Cited by 1SourcePDFScholar
2020

ProbAnch: a Modular Probabilistic Anchoring Framework

IJCAI 2020poster

Modeling object representations derived from perceptual observations, in a way that is also semantically meaningful for humans as well as autonomous agents, is a prerequisite for joint human-agent understanding of the world. A practical approach that aims to model such representations is perceptual…