When a Robot Reaches Out for Human Help. - Ignasi Andrés; Leliane Nunes de Barros; Denis Deratani Mauá; Thiago D. Simão (IBERAMIA, 2018)

Safe Policy Improvement with Baseline Bootstrapping in Factored Environments. - Thiago D. Simão; Matthijs T. J. Spaan (AAAI, 2019)

Safe and Sample-Efficient Reinforcement Learning Algorithms for Factored Environments. - Thiago D. Simão (IJCAI, 2019)

Structure Learning for Safe Policy Improvement. - Thiago D. Simão; Matthijs T. J. Spaan (IJCAI, 2019)

Safe Policy Improvement with an Estimated Baseline Policy. - Thiago D. Simão; Romain Laroche; Rémi Tachet des Combes (AAMAS, 2020)

WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning. - Qisong Yang; Thiago D. Simão; Simon H. Tindemans; Matthijs T. J. Spaan (AAAI, 2021)

AlwaysSafe: Reinforcement Learning without Safety Constraint Violations during Training. - Thiago D. Simão; Nils Jansen 001; Matthijs T. J. Spaan (AAMAS, 2021)

A Modern Perspective on Safe Automated Driving for Different Traffic Dynamics Using Constrained Reinforcement Learning. - Danial Kamran; Thiago D. Simão; Qisong Yang; Canmanie T. Ponnambalam; Johannes Fischer 007; Matthijs T. J. Spaan; Martin Lauer (ITSC, 2022)

Robust Anytime Learning of Markov Decision Processes. - Marnix Suilen; Thiago D. Simão; David Parker 001; Nils Jansen 001 (NeurIPS, 2022)

Safe Policy Improvement for POMDPs via Finite-State Controllers. - Thiago D. Simão; Marnix Suilen; Nils Jansen 001 (AAAI, 2023)

Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring. - Merlijn Krale; Thiago D. Simão; Nils Jansen 001 (ICAPS, 2023)

Reinforcement Learning by Guided Safe Exploration. - Qisong Yang; Thiago D. Simão; Nils Jansen 001; Simon H. Tindemans; Matthijs T. J. Spaan (ECAI, 2023)

Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking. - Dennis Gross; Thiago D. Simão; Nils Jansen 001; Guillermo A. Pérez 001 (ICAART (3), 2023)

Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation. - Yannick Hogewind; Thiago D. Simão; Tal Kachman; Nils Jansen 001 (ICLR, 2023)

Scalable Safe Policy Improvement via Monte Carlo Tree Search. - Alberto Castellini; Federico Bianchi 002; Edoardo Zorzi; Thiago D. Simão; Alessandro Farinelli; Matthijs T. J. Spaan (ICML, 2023)

Recursive Small-Step Multi-Agent A* for Dec-POMDPs. - Wietze Koops; Nils Jansen 001; Sebastian Junges; Thiago D. Simão (IJCAI, 2023)

More for Less: Safe Policy Improvement with Stronger Performance Guarantees. - Patrick Wienhöft; Marnix Suilen; Thiago D. Simão; Clemens Dubslaff; Christel Baier; Nils Jansen 001 (IJCAI, 2023)

Risk-aware curriculum generation for heavy-tailed task distributions. - Cevahir Köprülü; Thiago D. Simão; Nils Jansen 001; Ufuk Topcu (UAI, 2023)

Safe Online and Offline Reinforcement Learning. - Thiago D. Simão (2023)

Safety-constrained reinforcement learning with a distributional safety critic. - Qisong Yang; Thiago D. Simão; Simon H. Tindemans; Matthijs T. J. Spaan (Mach. Learn., 2023)

Supplementary Material for "Recursive Small-Step Multi-Agent A* for Dec-POMDPs". - Wietze Koops; Nils Jansen 001; Sebastian Junges; Thiago D. Simão (Zenodo, 2023)

Decision-making under uncertainty: beyond probabilities. - Thom S. Badings; Thiago D. Simão; Marnix Suilen; Nils Jansen 001 (Int. J. Softw. Tools Technol. Transf., 2023)

Factored Online Planning in Many-Agent POMDPs. - Maris F. L. Galesloot; Thiago D. Simão; Sebastian Junges; Nils Jansen 001 (AAAI, 2024)

Robust Active Measuring under Model Uncertainty. - Merlijn Krale; Thiago D. Simão; Jana Tumova; Nils Jansen 001 (AAAI, 2024)

A Supervised Learning Approach to Robust Reinforcement Learning for Job Shop Scheduling. - Christoph Schmidl; Thiago D. Simão; Nils Jansen 001 (ICAART (3), 2024)

Scalable Safe Policy Improvement for Factored Multi-Agent MDPs. - Federico Bianchi 002; Edoardo Zorzi; Alberto Castellini; Thiago D. Simão; Matthijs T. J. Spaan; Alessandro Farinelli (ICML, 2024)

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning. - Lisandro Arturo Jimenez-Roa; Thiago D. Simão; Zaharah Allah Bukhsh; Tiedo Tinga; Hajo Molegraaf; Nils Jansen 001; Mariëlle Stoelinga (CoRR, 2024)

Pessimistic Iterative Planning for Robust POMDPs. - Maris F. L. Galesloot; Marnix Suilen; Thiago D. Simão; Steven Carr 002; Matthijs T. J. Spaan; Ufuk Topcu; Nils Jansen 001 (CoRR, 2024)

Making Reinforcement Learning Safer via Curriculum Learning. - Kelvin Toonen; Thiago D. Simão (ICAART (3), 2025)

Safety-Prioritizing Curricula for Constrained Reinforcement Learning. - Cevahir Köprülü; Thiago D. Simão; Nils Jansen 001; Ufuk Topcu (ICLR, 2025)

Robust Transfer of Safety-Constrained Reinforcement Learning Agents. - Markel Zubia; Thiago D. Simão; Nils Jansen 001 (ICLR, 2025)

Tighter Value-Function Approximations for POMDPs. - Merlijn Krale; Wietze Koops; Sebastian Junges; Thiago D. Simão; Nils Jansen 001 (AAMAS, 2025)