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Denis Steckelmacher
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2020 – today
- 2024
- [j3]Gaoyuan Liu
, Joris De Winter
, Yuri Durodié
, Denis Steckelmacher
, Ann Nowé
, Bram Vanderborght
:
Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning. IEEE Robotics Autom. Lett. 9(6): 5974-5981 (2024) - 2023
- [j2]Mathieu Reymond
, Conor F. Hayes, Denis Steckelmacher
, Diederik M. Roijers, Ann Nowé
:
Actor-critic multi-objective reinforcement learning for non-linear utility functions. Auton. Agents Multi Agent Syst. 37(2): 23 (2023) - [j1]Gaoyuan Liu
, Joris De Winter
, Denis Steckelmacher
, Roshan Kumar Hota
, Ann Nowé
, Bram Vanderborght
:
Synergistic Task and Motion Planning With Reinforcement Learning-Based Non-Prehensile Actions. IEEE Robotics Autom. Lett. 8(5): 2764-2771 (2023) - [i10]Hélène Plisnier, Denis Steckelmacher, Jeroen Willems
, Bruno Depraetere, Ann Nowé:
Transferring Multiple Policies to Hotstart Reinforcement Learning in an Air Compressor Management Problem. CoRR abs/2301.12820 (2023) - [i9]Qingshuang Sun, Denis Steckelmacher, Yuan Yao, Ann Nowé, Raphaël Avalos:
Dynamic Size Message Scheduling for Multi-Agent Communication under Limited Bandwidth. CoRR abs/2306.10134 (2023) - 2022
- [c9]Jeroen Willems
, Kerem Eryilmaz, Denis Steckelmacher, Bruno Depraetere, Rian Beck, Abdellatif Bey-Temsamani, Jan Helsen, Ann Nowé:
Fast Initialization of Control Parameters using Supervised Learning on Data from Similar Assets. CCTA 2022: 1214-1221 - 2021
- [c8]Gaoyuan Liu
, Joris De Winter, Bram Vanderborght, Ann Nowé
, Denis Steckelmacher
:
MoveRL: To a Safer Robotic Reinforcement Learning Environment. BNAIC/BENELEARN 2021: 239-253 - [i8]Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé:
Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning. CoRR abs/2106.06009 (2021) - 2020
- [c7]Youri Coppens
, Denis Steckelmacher
, Catholijn M. Jonker
, Ann Nowé
:
Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning. TAILOR 2020: 163-179
2010 – 2019
- 2019
- [c6]Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. BNAIC/BENELEARN 2019 - [c5]Denis Steckelmacher, Hélène Plisnier, Ann Nowé:
A Motorized Wheelchair that Learns to Make its Way through a Crowd. BNAIC/BENELEARN 2019 - [c4]Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. BNAIC/BENELEARN 2019 - [c3]Axel Abels
, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. ICML 2019: 11-20 - [c2]Denis Steckelmacher
, Hélène Plisnier, Diederik M. Roijers
, Ann Nowé
:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. ECML/PKDD (3) 2019: 19-34 - [i7]Hélène Plisnier
, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
The Actor-Advisor: Policy Gradient With Off-Policy Advice. CoRR abs/1902.02556 (2019) - [i6]Denis Steckelmacher
, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. CoRR abs/1903.04193 (2019) - [i5]Hélène Plisnier
, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Learning Across Simulated Robots With Different Sensors. CoRR abs/1907.07958 (2019) - 2018
- [c1]Denis Steckelmacher, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Hélène Plisnier, Ann Nowé:
Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets. AAAI 2018: 4099-4106 - [i4]Hélène Plisnier, Denis Steckelmacher, Tim Brys, Diederik M. Roijers, Ann Nowé:
Directed Policy Gradient for Safe Reinforcement Learning with Human Advice. CoRR abs/1808.04096 (2018) - [i3]Axel Abels, Diederik M. Roijers, Tom Lenaerts, Ann Nowé, Denis Steckelmacher:
Dynamic Weights in Multi-Objective Deep Reinforcement Learning. CoRR abs/1809.07803 (2018) - 2017
- [i2]Denis Steckelmacher
, Diederik M. Roijers, Anna Harutyunyan, Peter Vrancx, Ann Nowé:
Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets. CoRR abs/1708.06551 (2017) - 2015
- [i1]Denis Steckelmacher, Peter Vrancx:
An Empirical Comparison of Neural Architectures for Reinforcement Learning in Partially Observable Environments. CoRR abs/1512.05509 (2015)
Coauthor Index
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last updated on 2024-08-05 20:18 CEST by the dblp team
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