159 citations · 329 across the 29 of their papers we have counts for
6 papers · 1 filter
EconoJax: A Fast & Scalable Economic Simulation in Jax
Koen Ponse, Aske Plaat, Niki van Stein +1
Accurate economic simulations often require many experimental runs, particularly when combined with reinforcement learning. Unfortunately, training reinforcement learning agents in…
Reset-free Reinforcement Learning with World Models
Zhao Yang, Thomas M. Moerland, Mike Preuss +2
Reinforcement learning (RL) is an appealing paradigm for training intelligent agents, enabling policy acquisition from the agent's own autonomously acquired experience. However, th…
Reinforcement Learning for Sustainable Energy: A Survey
Koen Ponse, Felix Kleuker, Márton Fejér +3
The transition to sustainable energy is a key challenge of our time, requiring modifications in the entire pipeline of energy production, storage, transmission, and consumption. At…
Towards General Negotiation Strategies with End-to-End Reinforcement Learning
Bram M. Renting, Thomas M. Moerland, Holger H. Hoos +1
The research field of automated negotiation has a long history of designing agents that can negotiate with other agents. Such negotiation strategies are traditionally based on manu…
Slot Structured World Models
Jonathan Collu, Riccardo Majellaro, Aske Plaat +1
The ability to perceive and reason about individual objects and their interactions is a goal to be achieved for building intelligent artificial systems. State-of-the-art approaches…
Explicitly Disentangled Representations in Object-Centric Learning
Riccardo Majellaro, Jonathan Collu, Aske Plaat +1
Extracting structured representations from raw visual data is an important and long-standing challenge in machine learning. Recently, techniques for unsupervised learning of object…