Giuseppe Paolo

Orcid: 0000-0003-4201-5967

According to our database1, Giuseppe Paolo authored at least 15 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

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Bibliography

2024
Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.
CoRR, 2024

A call for embodied AI.
CoRR, 2024

A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning.
CoRR, 2024

2023
Editorial to the "Evolutionary Reinforcement Learning" Special Issue.
ACM Trans. Evol. Learn. Optim., September, 2023

Multi-timestep models for Model-based Reinforcement Learning.
CoRR, 2023

2022
Guided Safe Shooting: model based reinforcement learning with safety constraints.
CoRR, 2022

Learning in Sparse Rewards settings through Quality-Diversity algorithms.
CoRR, 2022

2021
Learning in Sparse Rewards settings through Quality-Diversity algorithms. (Apprentissage par renforcement dans le cas de récompenses rares avec exploration par algorithmes de Qualité-Diversité et construction autonome d'espace d'état).
PhD thesis, 2021

Discovering and Exploiting Sparse Rewards in a Learned Behavior Space.
CoRR, 2021

Sparse reward exploration via novelty search and emitters.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020
Unsupervised Learning and Exploration of Reachable Outcome Space.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Novelty search makes evolvability inevitable.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2018
A Data-driven Model for Interaction-Aware Pedestrian Motion Prediction in Object Cluttered Environments.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017
Towards continuous control of flippers for a multi-terrain robot using deep reinforcement learning.
CoRR, 2017

Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017


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