Enrico Marchesini

Juan Antonio Rodríguez-Aguilar

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

On Stateful Value Factorization in Multi-Agent Reinforcement Learning.

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[DOI]

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Safe Entropic Agents under Team Constraints.

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[DOI]

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

An Approximate Embedding for Designing Ethical Reinforcement Learning Environments.

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Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Safe Multiagent Coordination via Entropic Exploration.

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[DOI]

CoRR, 2024

On Stateful Value Factorization in Multi-Agent Reinforcement Learning.

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[DOI]

CoRR, 2024

Entropy Seeking Constrained Multiagent Reinforcement Learning.

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[DOI]

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

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees.

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[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Entropy Maximization in High Dimensional Multiagent State Spaces.

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[DOI]

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.

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[DOI]

Luca Marzari

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Improving Deep Policy Gradients with Value Function Search.

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[DOI]

Christopher Amato

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Safe Deep Reinforcement Learning by Verifying Task-Level Properties.

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[DOI]

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.

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[DOI]

Frontiers Robotics AI, 2022

Curriculum learning for safe mapless navigation.

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[DOI]

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.

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[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Safety-informed mutations for evolutionary deep reinforcement learning.

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[DOI]

Christopher Amato

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.

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[DOI]

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.

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[DOI]

Alberto Castellini

Eng. Appl. Artif. Intell., 2021

Formal verification of neural networks for safety-critical tasks in deep reinforcement learning.

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[DOI]

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.

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[DOI]

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.

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[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation.

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[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning.

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[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Environment Properties in Partially Observable Monte Carlo Planning.

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[DOI]

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.

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[DOI]

CoRR, 2020

Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation.

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Proceedings of the Fourth IEEE International Conference on Robotic Computing, 2020

Discrete Deep Reinforcement Learning for Mapless Navigation.

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[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Explaining the Influence of Prior Knowledge on POMCP Policies.

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[DOI]

Proceedings of the Multi-Agent Systems and Agreement Technologies, 2020

Genetic Deep Reinforcement Learning for Mapless Navigation.

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[DOI]

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.

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[DOI]

Proceedings of the 3rd IEEE International Conference on Robotic Computing, 2019

Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities.

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[DOI]

Alberto Castellini