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ORCIDThiago D. Simão
Person information
- affiliation: Eindhoven University of Technology, The Netherlands
- affiliation (former): Radboud University, Nijmegen, The Netherlands
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2020 – today
- 2024
[c22]Maris F. L. Galesloot, Thiago D. Simão, Sebastian Junges, Nils Jansen:
Factored Online Planning in Many-Agent POMDPs. AAAI 2024: 17407-17415- [c21]Merlijn Krale, Thiago D. Simão, Jana Tumova, Nils Jansen:
Robust Active Measuring under Model Uncertainty. AAAI 2024: 21276-21284 - [c20]Christoph Schmidl, Thiago D. Simão, Nils Jansen:
A Supervised Learning Approach to Robust Reinforcement Learning for Job Shop Scheduling. ICAART (3) 2024: 1324-1335 - [c19]Federico Bianchi, Edoardo Zorzi, Alberto Castellini, Thiago D. Simão, Matthijs T. J. Spaan, Alessandro Farinelli:
Scalable Safe Policy Improvement for Factored Multi-Agent MDPs. ICML 2024 - [i13]Lisandro Arturo Jimenez-Roa, Thiago D. Simão, Zaharah Allah Bukhsh, Tiedo Tinga, Hajo Molegraaf, Nils Jansen, Mariëlle Stoelinga:
Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning. CoRR abs/2407.12894 (2024) - [i12]Maris F. L. Galesloot, Marnix Suilen, Thiago D. Simão, Steven Carr, Matthijs T. J. Spaan, Ufuk Topcu, Nils Jansen:
Pessimistic Iterative Planning for Robust POMDPs. CoRR abs/2408.08770 (2024) - 2023
- [b1]Thiago D. Simão
:
Safe Online and Offline Reinforcement Learning. Delft University of Technology, Netherlands, 2023 - [j2]Qisong Yang, Thiago D. Simão, Simon H. Tindemans, Matthijs T. J. Spaan:
Safety-constrained reinforcement learning with a distributional safety critic. Mach. Learn. 112(3): 859-887 (2023) - [j1]Thom S. Badings, Thiago D. Simão, Marnix Suilen, Nils Jansen:
Decision-making under uncertainty: beyond probabilities. Int. J. Softw. Tools Technol. Transf. 25(3): 375-391 (2023) - [c18]Thiago D. Simão, Marnix Suilen, Nils Jansen:
Safe Policy Improvement for POMDPs via Finite-State Controllers. AAAI 2023: 15109-15117 - [c17]Merlijn Krale, Thiago D. Simão, Nils Jansen:
Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring. ICAPS 2023: 212-220 - [c16]Qisong Yang, Thiago D. Simão, Nils Jansen, Simon H. Tindemans, Matthijs T. J. Spaan:
Reinforcement Learning by Guided Safe Exploration. ECAI 2023: 2858-2865 - [c15]Dennis Gross, Thiago D. Simão, Nils Jansen, Guillermo A. Pérez:
Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking. ICAART (3) 2023: 501-508 - [c14]Yannick Hogewind, Thiago D. Simão, Tal Kachman, Nils Jansen:
Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation. ICLR 2023 - [c13]Alberto Castellini, Federico Bianchi, Edoardo Zorzi, Thiago D. Simão, Alessandro Farinelli, Matthijs T. J. Spaan:
Scalable Safe Policy Improvement via Monte Carlo Tree Search. ICML 2023: 3732-3756 - [c12]Patrick Wienhöft, Marnix Suilen, Thiago D. Simão, Clemens Dubslaff, Christel Baier, Nils Jansen:
More for Less: Safe Policy Improvement with Stronger Performance Guarantees. IJCAI 2023: 4406-4415 - [c11]Wietze Koops, Nils Jansen, Sebastian Junges, Thiago D. Simão:
Recursive Small-Step Multi-Agent A* for Dec-POMDPs. IJCAI 2023: 5402-5410 - [c10]Cevahir Köprülü, Thiago D. Simão, Nils Jansen, Ufuk Topcu:
Risk-aware curriculum generation for heavy-tailed task distributions. UAI 2023: 1132-1142 - [i11]Thiago D. Simão, Marnix Suilen, Nils Jansen:
Safe Policy Improvement for POMDPs via Finite-State Controllers. CoRR abs/2301.04939 (2023) - [i10]Thom S. Badings, Thiago D. Simão, Marnix Suilen, Nils Jansen:
Decision-Making Under Uncertainty: Beyond Probabilities. CoRR abs/2303.05848 (2023) - [i9]Merlijn Krale, Thiago D. Simão, Nils Jansen:
Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring. CoRR abs/2303.08271 (2023) - [i8]Patrick Wienhöft, Marnix Suilen, Thiago D. Simão, Clemens Dubslaff, Christel Baier, Nils Jansen:
More for Less: Safe Policy Improvement With Stronger Performance Guarantees. CoRR abs/2305.07958 (2023) - [i7]Qisong Yang, Thiago D. Simão, Nils Jansen, Simon H. Tindemans, Matthijs T. J. Spaan:
Reinforcement Learning by Guided Safe Exploration. CoRR abs/2307.14316 (2023) - [i6]Merlijn Krale, Thiago D. Simão, Jana Tumova, Nils Jansen:
Robust Active Measuring under Model Uncertainty. CoRR abs/2312.11227 (2023) - [i5]Maris F. L. Galesloot, Thiago D. Simão, Sebastian Junges, Nils Jansen:
Factored Online Planning in Many-Agent POMDPs. CoRR abs/2312.11434 (2023) - 2022
- [c9]Danial Kamran, Thiago D. Simão, Qisong Yang, Canmanie T. Ponnambalam, Johannes Fischer, Matthijs T. J. Spaan, Martin Lauer:
A Modern Perspective on Safe Automated Driving for Different Traffic Dynamics Using Constrained Reinforcement Learning. ITSC 2022: 4017-4023 - [c8]Marnix Suilen, Thiago D. Simão, David Parker, Nils Jansen:
Robust Anytime Learning of Markov Decision Processes. NeurIPS 2022 - [i4]Marnix Suilen, Thiago D. Simão, Nils Jansen, David Parker:
Robust Anytime Learning of Markov Decision Processes. CoRR abs/2205.15827 (2022) - [i3]Yannick Hogewind, Thiago D. Simão, Tal Kachman, Nils Jansen:
Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation. CoRR abs/2210.01801 (2022) - [i2]Dennis Gross, Thiago D. Simão, Nils Jansen, Guillermo A. Pérez:
Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking. CoRR abs/2212.05337 (2022) - 2021
- [c7]Qisong Yang, Thiago D. Simão, Simon H. Tindemans, Matthijs T. J. Spaan:
WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning. AAAI 2021: 10639-10646 - [c6]Thiago D. Simão, Nils Jansen, Matthijs T. J. Spaan:
AlwaysSafe: Reinforcement Learning without Safety Constraint Violations during Training. AAMAS 2021: 1226-1235 - 2020
- [c5]Thiago D. Simão, Romain Laroche, Rémi Tachet des Combes:
Safe Policy Improvement with an Estimated Baseline Policy. AAMAS 2020: 1269-1277
2010 – 2019
- 2019
- [c4]Thiago D. Simão, Matthijs T. J. Spaan:
Safe Policy Improvement with Baseline Bootstrapping in Factored Environments. AAAI 2019: 4967-4974 - [c3]Thiago D. Simão, Matthijs T. J. Spaan:
Structure Learning for Safe Policy Improvement. IJCAI 2019: 3453-3459 - [c2]Thiago D. Simão:
Safe and Sample-Efficient Reinforcement Learning Algorithms for Factored Environments. IJCAI 2019: 6460-6461 - [i1]Thiago D. Simão, Romain Laroche, Rémi Tachet des Combes:
Safe Policy Improvement with an Estimated Baseline Policy. CoRR abs/1909.05236 (2019) - 2018
- [c1]Ignasi Andrés, Leliane Nunes de Barros, Denis Deratani Mauá, Thiago D. Simão:
When a Robot Reaches Out for Human Help. IBERAMIA 2018: 277-289
Coauthor Index
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last updated on 2024-11-05 20:58 CET by the dblp team
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