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Thomas M. Moerland
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2020 – today
- 2024
- [i24]Riccardo Majellaro, Jonathan Collu, Aske Plaat, Thomas M. Moerland:
Explicitly Disentangled Representations in Object-Centric Learning. CoRR abs/2401.10148 (2024) - [i23]Jonathan Collu, Riccardo Majellaro, Aske Plaat, Thomas M. Moerland:
Slot Structured World Models. CoRR abs/2402.03326 (2024) - [i22]Bram M. Renting, Thomas M. Moerland, Holger H. Hoos, Catholijn M. Jonker:
Towards General Negotiation Strategies with End-to-End Reinforcement Learning. CoRR abs/2406.15096 (2024) - [i21]Koen Ponse, Felix Kleuker, Márton Fejér, Álvaro Serra-Gómez, Aske Plaat, Thomas M. Moerland:
Reinforcement Learning for Sustainable Energy: A Survey. CoRR abs/2407.18597 (2024) - 2023
- [j6]Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
Model-based Reinforcement Learning: A Survey. Found. Trends Mach. Learn. 16(1): 1-118 (2023) - [j5]Mike Huisman
, Thomas M. Moerland, Aske Plaat, Jan N. van Rijn:
Are LSTMs good few-shot learners? Mach. Learn. 112(11): 4635-4662 (2023) - [c5]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Continuous Episodic Control. CoG 2023: 1-8 - [c4]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Two-Memory Reinforcement Learning. CoG 2023: 1-9 - [c3]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
First Go, then Post-Explore: The Benefits of Post-Exploration in Intrinsic Motivation. ICAART (2) 2023: 27-34 - [i20]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Two-Memory Reinforcement Learning. CoRR abs/2304.10098 (2023) - [i19]Jinke He, Thomas M. Moerland, Frans A. Oliehoek:
What model does MuZero learn? CoRR abs/2306.00840 (2023) - [i18]Mike Huisman, Thomas M. Moerland, Aske Plaat, Jan N. van Rijn:
Are LSTMs Good Few-Shot Learners? CoRR abs/2310.14139 (2023) - [i17]Thomas M. Moerland, Matthias Müller-Brockhausen, Zhao Yang, Andrius Bernatavicius, Koen Ponse, Tom Kouwenhoven, Andreas Sauter, Michiel van der Meer
, Bram M. Renting, Aske Plaat:
EduGym: An Environment Suite for Reinforcement Learning Education. CoRR abs/2311.10590 (2023) - 2022
- [j4]Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
A Unifying Framework for Reinforcement Learning and Planning. Frontiers Artif. Intell. 5 (2022) - [i16]Joery A. de Vries, Thomas M. Moerland, Aske Plaat:
On Credit Assignment in Hierarchical Reinforcement Learning. CoRR abs/2203.03292 (2022) - [i15]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
When to Go, and When to Explore: The Benefit of Post-Exploration in Intrinsic Motivation. CoRR abs/2203.16311 (2022) - [i14]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Continuous Episodic Control. CoRR abs/2211.15183 (2022) - [i13]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
First Go, then Post-Explore: the Benefits of Post-Exploration in Intrinsic Motivation. CoRR abs/2212.03251 (2022) - 2021
- [b1]Thomas M. Moerland:
The Intersection of Planning and Learning. Delft University of Technology, Netherlands, 2021 - [i12]Joery A. de Vries, Ken S. Voskuil, Thomas M. Moerland, Aske Plaat:
Visualizing MuZero Models. CoRR abs/2102.12924 (2021) - 2020
- [i11]Thomas M. Moerland, Anna Deichler, Simone Baldi, Joost Broekens, Catholijn M. Jonker:
Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning. CoRR abs/2005.07404 (2020) - [i10]Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
The Second Type of Uncertainty in Monte Carlo Tree Search. CoRR abs/2005.09645 (2020) - [i9]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
A Framework for Reinforcement Learning and Planning. CoRR abs/2006.15009 (2020) - [i8]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Model-based Reinforcement Learning: A Survey. CoRR abs/2006.16712 (2020)
2010 – 2019
- 2018
- [j3]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Emotion in reinforcement learning agents and robots: a survey. Mach. Learn. 107(2): 443-480 (2018) - [j2]Wouter Jan Wolfslag
, Mukunda Bharatheesha, Thomas M. Moerland, Martijn Wisse
:
RRT-CoLearn: Towards Kinodynamic Planning Without Numerical Trajectory Optimization. IEEE Robotics Autom. Lett. 3(3): 1655-1662 (2018) - [i7]Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
Monte Carlo Tree Search for Asymmetric Trees. CoRR abs/1805.09218 (2018) - [i6]Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
A0C: Alpha Zero in Continuous Action Space. CoRR abs/1805.09613 (2018) - [i5]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
The Potential of the Return Distribution for Exploration in RL. CoRR abs/1806.04242 (2018) - 2017
- [i4]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning. CoRR abs/1705.00470 (2017) - [i3]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Emotion in Reinforcement Learning Agents and Robots: A Survey. CoRR abs/1705.05172 (2017) - [i2]Wouter Wolfslag, Mukunda Bharatheesha, Thomas M. Moerland, Martijn Wisse:
RRT-CoLearn: towards kinodynamic planning without numerical trajectory optimization. CoRR abs/1710.10122 (2017) - [i1]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Efficient exploration with Double Uncertain Value Networks. CoRR abs/1711.10789 (2017) - 2016
- [c2]Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker:
Fear and Hope Emerge from Anticipation in Model-Based Reinforcement Learning. IJCAI 2016: 848-854 - [c1]Thomas M. Moerland, Aswin Chandarr, Maja Rudinac, Pieter P. Jonker:
Knowing What You Don't Know - Novelty Detection for Action Recognition in Personal Robots. VISIGRAPP (4: VISAPP) 2016: 317-327
2000 – 2009
- 2005
- [j1]Luiz Pessoa, Srikanth Padmala, Thomas M. Moerland:
Fate of unattended fearful faces in the amygdala is determined by both attentional resources and cognitive modulation. NeuroImage 28(1): 249-255 (2005)
Coauthor Index
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last updated on 2024-08-25 20:04 CEST by the dblp team
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