Bruno Lacerda
19 papers · 2011–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Reinforcement Learning
(13)
Artificial Intelligence
(11)
Machine Learning
(11)
Core AI
(10)
Methods
(9)
Applications
(7)
Optimization & Theory Β· Machine Learning
(7)
Learning Types
(5)
Bayesian & Probabilistic
(2)
Deep Learning
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Learning Paradigms
(1)
Optimization
(1)
Optimization & Theory Β· Deep Learning
(1)
Keywords
markov decision process
(5)
monte carlo tree search
(2)
gaussian process
(2)
reinforcement learning
(2)
model-based reinforcement learning
(2)
offline reinforcement learning
(2)
policy optimization
(1)
uncertainty quantification
(1)
robust planning
(1)
bayesian reinforcement learning
(1)
bellman equation
(1)
epistemic uncertainty
(1)
adversarial training
(1)
human-robot interaction
(1)
policy gradient
(1)
exploration-exploitation tradeoff
(1)
bayesian inference
(1)
mechanism design
(1)
bayesian learning
(1)
sample efficiency
(1)
Papers
Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics
AAAI 2026
A Finite-State Controller Based Offline Solver for Deterministic POMDPs
IJCAI 2025
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
ICML 2025
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
NeurIPS 2024
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
NeurIPS 2024
Stop! Planner Time: Metareasoning for Probabilistic Planning Using Learned Performance Profiles
AAAI 2024
Monte Carlo Tree Search with Boltzmann Exploration
NeurIPS 2023
Multi-Unit Auctions for Allocating Chance-Constrained Resources
AAAI 2023
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning
NeurIPS 2023
Planning with Hidden Parameter Polynomial MDPs
AAAI 2023
Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments
CoRL 2022
RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning
NeurIPS 2022
Shared Autonomy Systems with Stochastic Operator Models
IJCAI 2022
Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes
AAAI 2021
Risk-Averse Bayes-Adaptive Reinforcement Learning
NeurIPS 2021
Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes
CoRL 2020
Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints
IJCAI 2019
Optimal Policy Generation for Partially Satisfiable Co-Safe LTL Specifications
IJCAI 2015
Designing Petri Net Supervisors from LTL Specifications
RSS 2011