Enrico Marchesini

Orcid: 0000-0003-1858-7279

According to our database1, Enrico Marchesini authored at least 27 papers between 2019 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:

On csauthors.net:

Bibliography

2024
On Stateful Value Factorization in Multi-Agent Reinforcement Learning.
CoRR, 2024

Improving Policy Optimization via ε-Retrain.
CoRR, 2024

Entropy Seeking Constrained Multiagent Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Entropy Maximization in High Dimensional Multiagent State Spaces.
Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems, 2023

Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Improving Deep Policy Gradients with Value Function Search.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Safe Deep Reinforcement Learning by Verifying Task-Level Properties.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots.
Frontiers Robotics AI, 2022

Curriculum learning for safe mapless navigation.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Safety-informed mutations for evolutionary deep reinforcement learning.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Exploring Safer Behaviors for Deep Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Partially Observable Monte Carlo Planning with state variable constraints for mobile robot navigation.
Eng. Appl. Artif. Intell., 2021

Formal verification of neural networks for safety-critical tasks in deep reinforcement learning.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Environment Properties in Partially Observable Monte Carlo Planning.
Proceedings of the 8th Italian Workshop on Artificial Intelligence and Robotics co-located with the the 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021), 2021

2020
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification.
CoRR, 2020

Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation.
Proceedings of the Fourth IEEE International Conference on Robotic Computing, 2020

Discrete Deep Reinforcement Learning for Mapless Navigation.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Explaining the Influence of Prior Knowledge on POMCP Policies.
Proceedings of the Multi-Agent Systems and Agreement Technologies, 2020

Genetic Deep Reinforcement Learning for Mapless Navigation.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Double Deep Q-Network for Trajectory Generation of a Commercial 7DOF Redundant Manipulator.
Proceedings of the 3rd IEEE International Conference on Robotic Computing, 2019

Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities.
Proceedings of the 6th Italian Workshop on Artificial Intelligence and Robotics co-located with the XVIII International Conference of the Italian Association for Artificial Intelligence (AI*IA 2019), 2019


  Loading...