Florian Felten — accepted AI-conference papers

2025

EngiBench: A Framework for Data-Driven Engineering Design Research

Florian Felten, Gabriel Apaza, Gerhard Bräunlich, Cashen Diniz, XULIANG DONG, Arthur Drake +6

NeurIPS 2025poster

Engineering design optimization seeks to automatically determine the shapes, topologies, or parameters of components that maximize performance under given conditions. This process often depends on physics-based simulations, which are difficult to install, computationally expensive, and require domai…

Cited by 0 Source ↗Scholar ↗

2023

A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning

Florian Felten, Lucas Nunes Alegre, Ann Nowe, Ana L. C. Bazzan, El Ghazali Talbi, Grégoire Danoy +1

NeurIPS 2023poster

Multi-objective reinforcement learning algorithms (MORL) extend standard reinforcement learning (RL) to scenarios where agents must optimize multiple---potentially conflicting---objectives, each represented by a distinct reward function. To facilitate and accelerate research and benchmarking in mult…

Cited by 39 Source ↗PDF ↗code ↗Scholar ↗