2 papers
cs.RO2026
Scaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous Vehicles
Matteo Gallici, Ivan Masmitja, Mario MartÃn
Autonomous vehicles (AVs) offer a cost-effective solution for scientific missions such as underwater tracking. Reinforcement learning (RL) has emerged as a powerful method for cont…
cs.LG2025
Simplifying Deep Temporal Difference Learning
Matteo Gallici, Mattie Fellows, Benjamin Ellis +4
Q-learning played a foundational role in the field reinforcement learning (RL). However, TD algorithms with off-policy data, such as Q-learning, or nonlinear function approximation…