Denis Steckelmacher

According to our database, Denis Steckelmacher authored at least 19 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Dynamic Size Message Scheduling for Multi-Agent Communication Under Limited Bandwidth.

Qingshuang Sun, Denis Steckelmacher, Yuan Yao, Ann Nowé, Raphaël Avalos

IEEE Trans. Mob. Comput., December, 2024

Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning.

Gaoyuan Liu, Joris De Winter, Yuri Durodié, Denis Steckelmacher, Ann Nowé, Bram Vanderborght

IEEE Robotics Autom. Lett., June, 2024

Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution.

Senne Deproost, Denis Steckelmacher, Ann Nowé

CoRR, 2024

2023

Actor-critic multi-objective reinforcement learning for non-linear utility functions.

Mathieu Reymond, Conor F. Hayes, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé

Auton. Agents Multi Agent Syst., October, 2023

Synergistic Task and Motion Planning With Reinforcement Learning-Based Non-Prehensile Actions.

Gaoyuan Liu, Joris De Winter, Denis Steckelmacher, Roshan Kumar Hota, Ann Nowé, Bram Vanderborght

IEEE Robotics Autom. Lett., May, 2023

Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem.

Hélène Plisnier, Denis Steckelmacher, Jeroen Willems, Bruno Depraetere, Ann Nowé

CoRR, 2023

2022

Fast Initialization of Control Parameters using Supervised Learning on Data from Similar Assets.

Jeroen Willems, Kerem Eryilmaz, Denis Steckelmacher, Bruno Depraetere, Rian Beck, Abdellatif Bey-Temsamani, Jan Helsen, Ann Nowé

Proceedings of the IEEE Conference on Control Technology and Applications, 2022

2021

MoveRL: To a Safer Robotic Reinforcement Learning Environment.

Gaoyuan Liu, Joris De Winter, Bram Vanderborght, Ann Nowé, Denis Steckelmacher

Proceedings of the Artificial Intelligence and Machine Learning, 2021

2020

Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning.

Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé

Proceedings of the Trustworthy AI - Integrating Learning, Optimization and Reasoning, 2020

2019

Transfer Learning Across Simulated Robots With Different Sensors.

Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé

CoRR, 2019

The Actor-Advisor: Policy Gradient With Off-Policy Advice.

Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé

CoRR, 2019

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics.

Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Dynamic Weights in Multi-Objective Deep Reinforcement Learning.

Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher

Proceedings of the 36th International Conference on Machine Learning, 2019

A Motorized Wheelchair that Learns to Make its Way through a Crowd.

Denis Steckelmacher, Hélène Plisnier, Ann Nowé

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors.

Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice.

Hélène Plisnier, Denis Steckelmacher, Tim Brys, Diederik M. Roijers, Ann Nowé

CoRR, 2018

Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets.

Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Hélène Plisnier, Ann Nowé

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets.

Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Ann Nowé

CoRR, 2017

2015

An Empirical Comparison of Neural Architectures for Reinforcement Learning in Partially Observable Environments.

Denis Steckelmacher, Peter Vrancx

CoRR, 2015