Diogo S. Carvalho

According to our database, Diogo S. Carvalho authored at least 12 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Multi-Bellman operator for convergence of <i>Q</i>-learning with linear function approximation.

Diogo S. Carvalho, Pedro A. Santos, Francisco S. Melo

Trans. Mach. Learn. Res., 2025

Centralized training with hybrid execution in multi-agent reinforcement learning via predictive observation imputation.

Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo

Artif. Intell., 2025

Reinforcement learning in convergently non-stationary environments: Feudal hierarchies and learned representations.

Diogo S. Carvalho, Pedro A. Santos, Francisco S. Melo

Artif. Intell., 2025

Optimizing 2D Packing Strategies for Autoclave Loading Using Deep Reinforcement Learning.

Victor Ulisses Pugliese, Diogo S. Carvalho, Oséias Faria de Arruda Ferreira, Fábio Augusto Faria, Francisco S. Melo

Proceedings of the Progress in Artificial Intelligence, 2025

2024

The impact of data distribution on Q-learning with function approximation.

Pedro P. Santos, Diogo S. Carvalho, Alberto Sardinha, Francisco S. Melo

Mach. Learn., September, 2024

Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning.

Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Multi-Bellman operator for convergence of Q-learning with linear function approximation.

Diogo S. Carvalho, Pedro A. Santos, Francisco S. Melo

CoRR, 2023

Theoretical Remarks on Feudal Hierarchies and Reinforcement Learning.

Diogo S. Carvalho, Francisco S. Melo, Pedro A. Santos

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

Hierarchically Structured Scheduling and Execution of Tasks in a Multi-agent Environment.

Diogo S. Carvalho, Biswa Sengupta

Proceedings of the Progress in Artificial Intelligence, 2022

2021

Understanding the Impact of Data Distribution on Q-learning with Function Approximation.

Pedro P. Santos, Francisco S. Melo, Alberto Sardinha, Diogo S. Carvalho

CoRR, 2021

CHARET: Character-centered Approach to Emotion Tracking in Stories.

Diogo S. Carvalho, Joana Campos, Manuel Guimarães, Ana Antunes, João Dias, Pedro A. Santos

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

A new convergent variant of Q-learning with linear function approximation.

Diogo S. Carvalho, Francisco S. Melo, Pedro Santos

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020