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ORCIDAlberto Maria Metelli
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2020 – today
- 2022
[b1]Alberto Maria Metelli:
Exploiting environment configurability in reinforcement learning. Polytechnic University of Milan, Italy, Frontiers in Artificial Intelligence and Applications 361, IOS Press 2022, ISBN 978-1-64368-362-1- [j7]Alberto Maria Metelli:
A unified view of configurable Markov Decision Processes: Solution concepts, value functions, and operators. Intelligenza Artificiale 16(2): 165-184 (2022) - [j6]Alberto Maria Metelli
, Guglielmo Manneschi, Marcello Restelli:
Policy space identification in configurable environments. Mach. Learn. 111(6): 2093-2145 (2022) - [c18]Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli:
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization. AAAI 2022: 7525-7533 - [c17]Angelo Damiani, Giorgio Manganini, Alberto Maria Metelli, Marcello Restelli:
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning. ICML 2022: 4618-4629 - [c16]Alberto Maria Metelli, Francesco Trovò, Matteo Pirola, Marcello Restelli:
Stochastic Rising Bandits. ICML 2022: 15421-15457 - [c15]Julen Cestero, Marco Quartulli, Alberto Maria Metelli, Marcello Restelli:
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. IJCNN 2022: 1-9 - [i16]Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli:
ARLO: A Framework for Automated Reinforcement Learning. CoRR abs/2205.10416 (2022) - [i15]Julen Cestero, Marco Quartulli, Alberto Maria Metelli, Marcello Restelli:
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. CoRR abs/2207.03851 (2022) - [i14]Riccardo Poiani, Ciprian Stirbu, Alberto Maria Metelli, Marcello Restelli:
Optimizing Empty Container Repositioning and Fleet Deployment via Configurable Semi-POMDPs. CoRR abs/2207.12509 (2022) - [i13]Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Dynamical Linear Bandits. CoRR abs/2211.08997 (2022) - [i12]Luca Sabbioni, Luca Al Daire, Lorenzo Bisi, Alberto Maria Metelli, Marcello Restelli:
Simultaneously Updating All Persistence Values in Reinforcement Learning. CoRR abs/2211.11620 (2022) - [i11]Alberto Maria Metelli, Francesco Trovò, Matteo Pirola, Marcello Restelli:
Stochastic Rising Bandits. CoRR abs/2212.03798 (2022) - [i10]Davide Maran, Alberto Maria Metelli, Marcello Restelli:
Tight Performance Guarantees of Imitator Policies with Continuous Actions. CoRR abs/2212.03922 (2022) - [i9]Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli:
Autoregressive Bandits. CoRR abs/2212.06251 (2022) - 2021
- [j5]Alberto Maria Metelli, Matteo Pirotta, Daniele Calandriello, Marcello Restelli:
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach. J. Mach. Learn. Res. 22: 97:1-97:83 (2021) - [j4]Amarildo Likmeta, Alberto Maria Metelli, Giorgia Ramponi, Andrea Tirinzoni, Matteo Giuliani, Marcello Restelli:
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems. Mach. Learn. 110(9): 2541-2576 (2021) - [c14]Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli:
Policy Optimization as Online Learning with Mediator Feedback. AAAI 2021: 8958-8966 - [c13]Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli:
Provably Efficient Learning of Transferable Rewards. ICML 2021: 7665-7676 - [c12]Alberto Maria Metelli, Alessio Russo, Marcello Restelli:
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning. NeurIPS 2021: 8119-8132 - [c11]Giorgia Ramponi, Alberto Maria Metelli, Alessandro Concetti, Marcello Restelli:
Learning in Non-Cooperative Configurable Markov Decision Processes. NeurIPS 2021: 22808-22821 - [i8]Pierre Liotet, Francesco Vidaich, Alberto Maria Metelli, Marcello Restelli:
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization. CoRR abs/2112.06625 (2021) - 2020
- [j3]Alberto Maria Metelli, Matteo Pirotta, Marcello Restelli:
On the use of the policy gradient and Hessian in inverse reinforcement learning. Intelligenza Artificiale 14(1): 117-150 (2020) - [j2]Alberto Maria Metelli, Matteo Papini, Nico Montali, Marcello Restelli:
Importance Sampling Techniques for Policy Optimization. J. Mach. Learn. Res. 21: 141:1-141:75 (2020) - [j1]Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Riccardo Giol, Marcello Restelli, Danilo Romano:
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. Robotics Auton. Syst. 131: 103568 (2020) - [c10]Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli:
Gradient-Aware Model-Based Policy Search. AAAI 2020: 3801-3808 - [c9]Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli:
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. AISTATS 2020: 2359-2369 - [c8]Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli:
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning. ICML 2020: 6862-6873 - [i7]Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli:
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning. CoRR abs/2002.06836 (2020) - [i6]Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli:
Policy Optimization as Online Learning with Mediator Feedback. CoRR abs/2012.08225 (2020)
2010 – 2019
- 2019
- [c7]Alberto Maria Metelli, Emanuele Ghelfi, Marcello Restelli:
Reinforcement Learning in Configurable Continuous Environments. ICML 2019: 4546-4555 - [c6]Matteo Papini, Alberto Maria Metelli, Lorenzo Lupo, Marcello Restelli:
Optimistic Policy Optimization via Multiple Importance Sampling. ICML 2019: 4989-4999 - [c5]Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli:
Feature Selection via Mutual Information: New Theoretical Insights. IJCNN 2019: 1-9 - [c4]Alberto Maria Metelli, Amarildo Likmeta, Marcello Restelli:
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters. NeurIPS 2019: 4335-4347 - [i5]Mario Beraha, Alberto Maria Metelli, Matteo Papini, Andrea Tirinzoni, Marcello Restelli:
Feature Selection via Mutual Information: New Theoretical Insights. CoRR abs/1907.07384 (2019) - [i4]Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli:
Policy Space Identification in Configurable Environments. CoRR abs/1909.03984 (2019) - [i3]Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni, Matteo Papini, Marcello Restelli:
Gradient-Aware Model-based Policy Search. CoRR abs/1909.04115 (2019) - 2018
- [c3]Alberto Maria Metelli, Mirco Mutti, Marcello Restelli:
Configurable Markov Decision Processes. ICML 2018: 3488-3497 - [c2]Alberto Maria Metelli, Matteo Papini, Francesco Faccio, Marcello Restelli:
Policy Optimization via Importance Sampling. NeurIPS 2018: 5447-5459 - [i2]Alberto Maria Metelli, Mirco Mutti, Marcello Restelli:
Configurable Markov Decision Processes. CoRR abs/1806.05415 (2018) - [i1]Alberto Maria Metelli, Matteo Papini, Francesco Faccio, Marcello Restelli:
Policy Optimization via Importance Sampling. CoRR abs/1809.06098 (2018) - 2017
- [c1]Alberto Maria Metelli, Matteo Pirotta, Marcello Restelli:
Compatible Reward Inverse Reinforcement Learning. NIPS 2017: 2050-2059
Coauthor Index
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