Mirco Mutti

According to our database, Mirco Mutti authored at least 16 papers between 2018 and 2024.

Collaborative distances:

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

2024

Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms.

Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli

CoRR, 2024

A Framework for Partially Observed Reward-States in RLHF.

Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano, Ambuj Tewari

CoRR, 2024

2023

Unsupervised reinforcement learning via state entropy maximization.

Mirco Mutti

PhD thesis, 2023

Convex Reinforcement Learning in Finite Trials.

Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

J. Mach. Learn. Res., 2023

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.

Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

CoRR, 2023

Persuading Farsighted Receivers in MDPs: the Power of Honesty.

Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Tale of Sampling and Estimation in Discounted Reinforcement Learning.

Alberto Maria Metelli, Mirco Mutti, Marcello Restelli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization.

Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Challenging Common Assumptions in Convex Reinforcement Learning.

Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Importance of Non-Markovianity in Maximum State Entropy Exploration.

Mirco Mutti, Riccardo De Santi, Marcello Restelli

Proceedings of the International Conference on Machine Learning, 2022

Reward-Free Policy Space Compression for Reinforcement Learning.

Mirco Mutti, Stefano Del Col, Marcello Restelli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Unsupervised Reinforcement Learning in Multiple Environments.

Mirco Mutti, Mattia Mancassola, Marcello Restelli

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate.

Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Policy Gradient Method for Task-Agnostic Exploration.

Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

CoRR, 2020

An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies.

Mirco Mutti, Marcello Restelli

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018

Configurable Markov Decision Processes.

Alberto Maria Metelli, Mirco Mutti, Marcello Restelli

Proceedings of the 35th International Conference on Machine Learning, 2018