TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems. - Matteo Gallici; Mario Martin; Ivan Masmitja (AAMAS, 2023)

JaxMARL: Multi-Agent RL Environments in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (AAMAS, 2024)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Ravi Hammond; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; et al. (NeurIPS, 2024)

Simplifying Deep Temporal Difference Learning. - Matteo Gallici; Mattie Fellows; Benjamin Ellis; Bartomeu Pou; Ivan Masmitja; Jakob Nicolaus Foerster; Mario Martin (ICLR, 2025)

Scaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous Vehicles. - Matteo Gallici; Ivan Masmitja; Mario Martin (CoRR, 2025)

Fine-Tuning Next-Scale Visual Autoregressive Models with Group Relative Policy Optimization. - Matteo Gallici; Haitz Sáez de Ocáriz Borde (CoRR, 2025)

Ad-Hoc Human-AI Coordination Challenge. - Tin Dizdarevic; Ravi Hammond; Tobias Gessler; Anisoara Calinescu; Jonathan Cook 004; Matteo Gallici; Andrei Lupu; Darius Muglich; Johannes Forkel; Jakob Nicolaus Foerster (CoRR, 2025)