10 papers
Gaussian Process Aggregation for Root-Parallel Monte Carlo Tree Search with Continuous Actions
Junlin Xiao, Victor-Alexandru Darvariu, Bruno Lacerda +1
The paper introduces a Gaussian Process regression method to aggregate statistics across parallel Monte Carlo Tree Search threads for continuous-action environments, showing improv…
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
Alexander Rutherford, Benjamin Ellis, Matteo Gallici +18
Benchmarks are crucial in the development of machine learning algorithms, with available environments significantly influencing reinforcement learning (RL) research. Traditionally,…
Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
Alex Schutz, Victor-Alexandru Darvariu, Efimia Panagiotaki +2
Neural algorithmic reasoning (NAR) is a paradigm that trains neural networks to execute classic algorithms by supervised learning. Despite its successes, important limitations rema…
Ro-To-Go! Robust Reactive Control with Signal Temporal Logic
Roland Ilyes, Lara Brudermüller, Nick Hawes +1
Signal Temporal Logic (STL) robustness is a common objective for optimal robot control, but its dependence on history limits the robot's decision-making capabilities when used in M…
Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders
Victor-Alexandru Darvariu, Charlotte Z. Reed, Jan Stratmann +21
Underwater glider robots have become indispensable for ocean sampling, yet fully autonomous long-term operation remains rare in practice. Although stakeholders are calling for tool…
Improving Regret Approximation for Unsupervised Dynamic Environment Generation
Harry Mead, Bruno Lacerda, Jakob Foerster +1
Unsupervised Environment Design (UED) seeks to automatically generate training curricula for reinforcement learning (RL) agents, with the goal of improving generalisation and zero-…