Giorgio Angelotti

According to our database, Giorgio Angelotti authored at least 10 papers between 2020 and 2024.

Collaborative distances:

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

2024

Offline Risk-sensitive RL with Partial Observability to Enhance Performance in Human-Robot Teaming.

Giorgio Angelotti, Caroline P. C. Chanel, Adam H. M. Pinto, Christophe Lounis, Corentin Chauffaut, Nicolas Drougard

CoRR, 2024

2023

Advances in Risk-Aware Offline Reinforcement Learning: A Study of Data Augmentation, Explainability, and Policy Selection. (Contributions à l'apprentissage par renforcement hors ligne avec prise en compte du risque : étude sur l'augmentation des données, sur la sélection des politiques et sur l'explicabilité).

Giorgio Angelotti

PhD thesis, 2023

Towards a more efficient computation of individual attribute and policy contribution for post-hoc explanation of cooperative multi-agent systems using Myerson values.

Giorgio Angelotti, Natalia Díaz Rodríguez

Knowl. Based Syst., 2023

HyPE: Attention with Hyperbolic Biases for Relative Positional Encoding.

Giorgio Angelotti

CoRR, 2023

Data-Efficient Offline Reinforcement Learning with Approximate Symmetries.

Giorgio Angelotti, Nicolas Drougard, Caroline P. C. Chanel

Proceedings of the Agents and Artificial Intelligence - 15th International Conference, 2023

Data Augmentation Through Expert-Guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning.

Giorgio Angelotti, Nicolas Drougard, Caroline P. C. Chanel

Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023

2022

Expert-guided Symmetry Detection in Markov Decision Processes.

Giorgio Angelotti, Nicolas Drougard, Caroline P. C. Chanel

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021

Exploiting Expert-guided Symmetry Detection in Markov Decision Processes.

Giorgio Angelotti, Nicolas Drougard, Caroline P. C. Chanel

CoRR, 2021

Exploitation vs Caution: Risk-sensitive Policies for Offline Learning.

Giorgio Angelotti, Nicolas Drougard, Caroline Ponzoni Carvalho Chanel

CoRR, 2021

2020

Offline Learning for Planning: A Summary.

Giorgio Angelotti, Nicolas Drougard, Caroline Ponzoni Carvalho Chanel

CoRR, 2020