Thiago D. Simão

According to our database, Thiago D. Simão authored at least 27 papers between 2018 and 2024.

Collaborative distances:

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

2024

Pessimistic Iterative Planning for Robust POMDPs.

Maris F. L. Galesloot, Marnix Suilen, Thiago D. Simão, Steven Carr, Matthijs T. J. Spaan, Ufuk Topcu, Nils Jansen

CoRR, 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, Mariëlle Stoelinga

CoRR, 2024

Scalable Safe Policy Improvement for Factored Multi-Agent MDPs.

Federico Bianchi, Edoardo Zorzi, Alberto Castellini, Thiago D. Simão, Matthijs T. J. Spaan, Alessandro Farinelli

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Supervised Learning Approach to Robust Reinforcement Learning for Job Shop Scheduling.

Christoph Schmidl, Thiago D. Simão, Nils Jansen

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

Robust Active Measuring under Model Uncertainty.

Merlijn Krale, Thiago D. Simão, Jana Tumova, Nils Jansen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Factored Online Planning in Many-Agent POMDPs.

Maris F. L. Galesloot, Thiago D. Simão, Sebastian Junges, Nils Jansen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Decision-making under uncertainty: beyond probabilities.

Thom S. Badings, Thiago D. Simão, Marnix Suilen, Nils Jansen

Int. J. Softw. Tools Technol. Transf., June, 2023

Safety-constrained reinforcement learning with a distributional safety critic.

Qisong Yang, Thiago D. Simão, Simon H. Tindemans, Matthijs T. J. Spaan

Mach. Learn., March, 2023

Safe Online and Offline Reinforcement Learning.

Thiago D. Simão

PhD thesis, 2023

Risk-aware curriculum generation for heavy-tailed task distributions.

Cevahir Köprülü, Thiago D. Simão, Nils Jansen, Ufuk Topcu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

More for Less: Safe Policy Improvement with Stronger Performance Guarantees.

Patrick Wienhöft, Marnix Suilen, Thiago D. Simão, Clemens Dubslaff, Christel Baier, Nils Jansen

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Recursive Small-Step Multi-Agent A* for Dec-POMDPs.

Wietze Koops, Nils Jansen, Sebastian Junges, Thiago D. Simão

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Scalable Safe Policy Improvement via Monte Carlo Tree Search.

Alberto Castellini, Federico Bianchi, Edoardo Zorzi, Thiago D. Simão, Alessandro Farinelli, Matthijs T. J. Spaan

Proceedings of the International Conference on Machine Learning, 2023

Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation.

Yannick Hogewind, Thiago D. Simão, Tal Kachman, Nils Jansen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking.

Dennis Gross, Thiago D. Simão, Nils Jansen, Guillermo A. Pérez

Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023

Reinforcement Learning by Guided Safe Exploration.

Qisong Yang, Thiago D. Simão, Nils Jansen, Simon H. Tindemans, Matthijs T. J. Spaan

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring.

Merlijn Krale, Thiago D. Simão, Nils Jansen

Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling, 2023

Safe Policy Improvement for POMDPs via Finite-State Controllers.

Thiago D. Simão, Marnix Suilen, Nils Jansen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Robust Anytime Learning of Markov Decision Processes.

Marnix Suilen, Thiago D. Simão, David Parker, Nils Jansen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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, Matthijs T. J. Spaan, Martin Lauer

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2021

AlwaysSafe: Reinforcement Learning without Safety Constraint Violations during Training.

Thiago D. Simão, Nils Jansen, Matthijs T. J. Spaan

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning.

Qisong Yang, Thiago D. Simão, Simon H. Tindemans, Matthijs T. J. Spaan

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Safe Policy Improvement with an Estimated Baseline Policy.

Thiago D. Simão, Romain Laroche, Rémi Tachet des Combes

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Structure Learning for Safe Policy Improvement.

Thiago D. Simão, Matthijs T. J. Spaan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Safe and Sample-Efficient Reinforcement Learning Algorithms for Factored Environments.

Thiago D. Simão

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Safe Policy Improvement with Baseline Bootstrapping in Factored Environments.

Thiago D. Simão, Matthijs T. J. Spaan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

When a Robot Reaches Out for Human Help.

Ignasi Andrés, Leliane Nunes de Barros, Denis Deratani Mauá, Thiago D. Simão

Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2018, 2018