Lacerda, Bruno

20 publications

IJCAI 2025 A Finite-State Controller Based Offline Solver for Deterministic POMDPs Alex Schutz, Yang You, Matías Mattamala, Ipek Caliskanelli, Bruno Lacerda, Nick Hawes

NeurIPS 2025 Improving Regret Approximation for Unsupervised Dynamic Environment Generation Harry Mead, Bruno Lacerda, Jakob Nicolaus Foerster, Nick Hawes

ICML 2025 Return Capping: Sample Efficient CVaR Policy Gradient Optimisation Harry Mead, Clarissa Costen, Bruno Lacerda, Nick Hawes

NeurIPS 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Foerster

NeurIPS 2024 No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery Alex Rutherford, Michael Beukman, Timon Willi, Bruno Lacerda, Nick Hawes, Jakob Foerster

JAIR 2024 Right Place, Right Time: Proactive Multi-Robot Task Allocation Under Spatiotemporal Uncertainty Charlie Street, Bruno Lacerda, Manuel Mühlig, Nick Hawes

AAAI 2024 Stop! Planner Time: Metareasoning for Probabilistic Planning Using Learned Performance Profiles Matthew Budd, Bruno Lacerda, Nick Hawes

NeurIPSW 2023 JaxMARL: Multi-Agent RL Environments in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster

NeurIPS 2023 Monte Carlo Tree Search with Boltzmann Exploration Michael Painter, Mohamed Baioumy, Nick Hawes, Bruno Lacerda

AAAI 2023 Multi-Unit Auctions for Allocating Chance-Constrained Resources Anna Gautier, Bruno Lacerda, Nick Hawes, Michael J. Wooldridge

NeurIPS 2023 One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning Marc Rigter, Bruno Lacerda, Nick Hawes

AAAI 2023 Planning with Hidden Parameter Polynomial MDPs Clarissa Costen, Marc Rigter, Bruno Lacerda, Nick Hawes

CoRL 2022 Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments Matthew Budd, Paul Duckworth, Nick Hawes, Bruno Lacerda

NeurIPS 2022 RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning Marc Rigter, Bruno Lacerda, Nick Hawes

IJCAI 2022 Shared Autonomy Systems with Stochastic Operator Models Clarissa Costen, Marc Rigter, Bruno Lacerda, Nick Hawes

AAAI 2021 Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes Marc Rigter, Bruno Lacerda, Nick Hawes

NeurIPS 2021 Risk-Averse Bayes-Adaptive Reinforcement Learning Marc Rigter, Bruno Lacerda, Nick Hawes

CoRL 2020 Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes Paul Duckworth, Bruno Lacerda, Nick Hawes

IJCAI 2019 Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints Masoumeh Mansouri, Bruno Lacerda, Nick Hawes, Federico Pecora

IJCAI 2015 Optimal Policy Generation for Partially Satisfiable Co-Safe LTL Specifications Bruno Lacerda, David Parker, Nick Hawes