Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning. - João G. Ribeiro; Francisco S. Melo; João Dias 001 (GCAI, 2019)

Pruning and Sparsemax Methods for Hierarchical Attention Networks. - João G. Ribeiro; Frederico S. Felisberto; Isabel Neto (CoRR, 2020)

Helping People on the Fly: Ad Hoc Teamwork for Human-Robot Teams. - João G. Ribeiro; Miguel Faria 001; Alberto Sardinha; Francisco S. Melo (EPIA, 2021)

Ad Hoc Teamwork in the Presence of Non-stationary Teammates. - Pedro M. Santos 002; João G. Ribeiro; Alberto Sardinha; Francisco S. Melo (EPIA, 2021)

Assisting Unknown Teammates in Unknown Tasks: Ad Hoc Teamwork under Partial Observability. - João G. Ribeiro; Cassandro Martinho; Alberto Sardinha; Francisco S. Melo (CoRR, 2022)

Making Friends in the Dark: Ad Hoc Teamwork Under Partial Observability. - João G. Ribeiro; Cassandro Martinho; Alberto Sardinha; Francisco S. Melo (ECAI, 2023)

TEAMSTER: Model-based reinforcement learning for ad hoc teamwork. - João G. Ribeiro; Gonçalo Rodrigues; Alberto Sardinha; Francisco S. Melo (Artif. Intell., 2023)

TEAMSTER: Model-Based Reinforcement Learning for Ad Hoc Teamwork (Abstract Reprint). - João G. Ribeiro; Gonçalo Rodrigues; Alberto Sardinha; Francisco S. Melo (AAAI, 2024)

A Middleware Architecture for Enhancing Multimedia Flows with High-Level Semantic Information. - José Matheus Carvalho Boaro; Polyana Bezerra da Costa; Daniel de Sousa Moraes; Pedro Thiago Cutrim dos Santos; João G. Ribeiro; Julio Cesar Duarte; Alberto Sardinha; Sérgio Colcher (IMX Workshops, 2024)

RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains. - João G. Ribeiro; Yaniv Oren; Alberto Sardinha; Matthijs T. J. Spaan; Francisco S. Melo (CoRR, 2025)