Concepts for Anchoring in Robotics. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (AI*IA, 2001)

Fun2Mas: The Milan Robocup Team. - Andrea Bonarini; Giovanni Invernizzi; Fabio M. Marchese; Matteo Matteucci; Marcello Restelli; Domenico G. Sorrenti (RoboCup, 2001)

A Framework for Robust Sensing in Multi-agent Systems. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (RoboCup, 2001)

An architecture to implement agents co-operating in dynamic environments. - Andrea Bonarini; Marcello Restelli (AAMAS, 2002)

A robot localization method based on evidence accumulation and multi-resolution. - Marcello Restelli; Domenico G. Sorrenti; Fabio M. Marchese (IROS, 2002)

MUREA: A MUlti-Resolution Evidence Accumulation Method for Robot Localization in Known Environments. - Marcello Restelli; Domenico G. Sorrenti; Fabio M. Marchese (RoboCup, 2002)

Filling the Gap among Coordination, Planning, and Reaction Using a Fuzzy Cognitive Model. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (RoboCup, 2003)

A Probabilistic Framework for Weighting Different Sensor Data in MUREA. - Marcello Restelli; Domenico G. Sorrenti; Fabio M. Marchese (RoboCup, 2003)

Dead Reckoning for Mobile Robots Using Two Optical Mice. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (ICINCO (2), 2004)

A kinematic-independent dead-reckoning sensor for indoor mobile robotics. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (IROS, 2004)

A multi-agent system for multi-agent learning. - Marcello Restelli (2004)

Automatic Error Detection and Reduction for an Odometric Sensor based on Two Optical Mice. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (ICRA, 2005)

MRT: Robotics Off-the-Shelf with the Modular Robotic Toolkit. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (PPSDR@ICRA, 2005)

Reinforcement Distribution in Continuous State Action Space Fuzzy Q-Learning: A Novel Approach. - Andrea Bonarini; Francesco Montrone; Marcello Restelli (WILF, 2005)

Learning to cooperate in multi-agent social dilemmas. - Enrique Munoz de Cote; Alessandro Lazaric; Marcello Restelli (AAMAS, 2006)

Incremental Skill Acquisition for Self-motivated Learning Animats. - Andrea Bonarini; Alessandro Lazaric; Marcello Restelli (SAB, 2006)

Concepts and fuzzy models for behavior-based robotics. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (Int. J. Approx. Reason., 2006)

Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game. - Alessandro Lazaric; Enrique Munoz de Cote; Fabio Dercole; Marcello Restelli (Adaptive Agents and Multi-Agents Systems, 2007)

Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions. - Andrea Bonarini; Alessandro Lazaric; Marcello Restelli (AI*IA, 2007)

Piecewise constant reinforcement learning for robotic applications. - Andrea Bonarini; Alessandro Lazaric; Marcello Restelli (ICINCO-ICSO, 2007)

Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods. - Alessandro Lazaric; Marcello Restelli; Andrea Bonarini (NIPS, 2007)

Learning Fuzzy Classifier Systems: Architecture and Exploration Issues. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (Int. J. Artif. Intell. Tools, 2007)

Problems and solutions for anchoring in multi-robot applications. - Andrea Bonarini; Matteo Matteucci; Marcello Restelli (J. Intell. Fuzzy Syst., 2007)

Towards Automated Bargaining in Electronic Markets: A Partially Two-Sided Competition Model. - Nicola Gatti 001; Alessandro Lazaric; Marcello Restelli (AMEC/TADA, 2008)

Transfer of task representation in reinforcement learning using policy-based proto-value functions. - Eliseo Ferrante; Alessandro Lazaric; Marcello Restelli (AAMAS (3), 2008)

On the usefulness of opponent modeling: the Kuhn Poker case study. - Alessandro Lazaric; Mario Quaresimale; Marcello Restelli (AAMAS (3), 2008)

Transfer of samples in batch reinforcement learning. - Alessandro Lazaric; Marcello Restelli; Andrea Bonarini (ICML, 2008)

Batch Reinforcement Learning for Controlling a Mobile Wheeled Pendulum Robot. - Andrea Bonarini; Claudio Caccia; Alessandro Lazaric; Marcello Restelli (IFIP AI, 2008)

Improving Batch Reinforcement Learning Performance through Transfer of Samples. - Alessandro Lazaric; Marcello Restelli; Andrea Bonarini (STAIRS, 2008)

Batch Reinforcement Learning for semi-active suspension control. - Simone Tognetti; Sergio M. Savaresi; Cristiano Spelta; Marcello Restelli (CCA/ISIC, 2009)

Batch Reinforcement Learning - An Application to a Controllable Semi-active Suspension System. - Simone Tognetti; Marcello Restelli; Sergio M. Savaresi; Cristiano Spelta (ICINCO-ICSO, 2009)

Reinforcement distribution in fuzzy Q-learning. - Andrea Bonarini; Alessandro Lazaric; Francesco Montrone; Marcello Restelli (Fuzzy Sets Syst., 2009)

Tree-based variable selection for dimensionality reduction of large-scale control systems. - Andrea Castelletti; Stefano Galelli; Marcello Restelli; Rodolfo Soncini-Sessa (ADPRL, 2011)

Fitted policy search. - Martino Migliavacca; Alessio Pecorino; Matteo Pirotta; Marcello Restelli; Andrea Bonarini (ADPRL, 2011)

Equilibrium approximation in simulation-based extensive-form games. - Nicola Gatti 001; Marcello Restelli (AAMAS, 2011)

Multi-objective fitted Q-iteration: Pareto frontier approximation in one single run. - Andrea Castelletti; Francesca Pianosi; Marcello Restelli (ICNSC, 2011)

Transfer from Multiple MDPs. - Alessandro Lazaric; Marcello Restelli (NIPS, 2011)

Computing Equilibria with Two-Player Zero-Sum Continuous Stochastic Games with Switching Controller. - Guido Bonomi; Nicola Gatti 001; Fabio Panozzo; Marcello Restelli (AAAI, 2012)

Tree-based Fitted Q-iteration for Multi-Objective Markov Decision problems. - Andrea Castelletti; Francesca Pianosi; Marcello Restelli (IJCNN, 2012)

Data-driven dynamic emulation modelling for the optimal management of environmental systems. - Andrea Castelletti; Stefano Galelli; Marcello Restelli; Rodolfo Soncini-Sessa (Environ. Model. Softw., 2012)

Efficient Evolutionary Dynamics with Extensive-Form Games. - Nicola Gatti 001; Fabio Panozzo; Marcello Restelli (AAAI, 2013)

Extensive-form games with heterogeneous populations. - Nicola Gatti 001; Fabio Panozzo; Marcello Restelli (AAMAS, 2013)

Safe Policy Iteration. - Matteo Pirotta; Marcello Restelli; Alessio Pecorino; Daniele Calandriello (ICML (3), 2013)

Adaptive Step-Size for Policy Gradient Methods. - Matteo Pirotta; Marcello Restelli; Luca Bascetta (NIPS, 2013)

Evolutionary Dynamics of Q-Learning over the Sequence Form. - Fabio Panozzo; Nicola Gatti 001; Marcello Restelli (AAAI, 2014)

Policy gradient approaches for multi-objective sequential decision making: A comparison. - Simone Parisi; Matteo Pirotta; Nicola Smacchia; Luca Bascetta; Marcello Restelli (ADPRL, 2014)

Policy gradient approaches for multi-objective sequential decision making. - Simone Parisi; Matteo Pirotta; Nicola Smacchia; Luca Bascetta; Marcello Restelli (IJCNN, 2014)

Multi-Objective Reinforcement Learning with Continuous Pareto Frontier Approximation. - Matteo Pirotta; Simone Parisi; Marcello Restelli (AAAI, 2015)

Estimating a Mean-Path from a set of 2-D curves. - Amir M. Ghalamzan E.; Luca Bascetta; Marcello Restelli; Paolo Rocco (ICRA, 2015)

Following Newton direction in Policy Gradient with parameter exploration. - Giorgio Manganini; Matteo Pirotta; Marcello Restelli; Luca Bascetta (IJCNN, 2015)

Sparse multi-task reinforcement learning. - Daniele Calandriello; Alessandro Lazaric; Marcello Restelli (Intelligenza Artificiale, 2015)

Policy gradient in Lipschitz Markov Decision Processes. - Matteo Pirotta; Marcello Restelli; Luca Bascetta (Mach. Learn., 2015)

Sequence-Form and Evolutionary Dynamics: Realization Equivalence to Agent Form and Logit Dynamics. - Nicola Gatti 001; Marcello Restelli (AAAI, 2016)

Inverse Reinforcement Learning through Policy Gradient Minimization. - Matteo Pirotta; Marcello Restelli (AAAI, 2016)

Budgeted Multi-Armed Bandit in Continuous Action Space. - Francesco Trovò; Stefano Paladino; Marcello Restelli; Nicola Gatti 001 (ECAI, 2016)

Estimating Maximum Expected Value through Gaussian Approximation. - Carlo D'Eramo; Marcello Restelli; Alessandro Nuara (ICML, 2016)

Reconstruction of public transport state. - Alessio Pagani; Francesco Bruschi; Vincenzo Rana; Marcello Restelli (ITSC, 2016)

Extensive-form games with heterogeneous populations: solution concepts, equilibria characterization, learning dynamics. - Nicola Gatti 001; Fabio Panozzo; Marcello Restelli (Intelligenza Artificiale, 2016)

Multi-objective Reinforcement Learning through Continuous Pareto Manifold Approximation. - Simone Parisi; Matteo Pirotta; Marcello Restelli (J. Artif. Intell. Res., 2016)

Policy Search for the Optimal Control of Markov Decision Processes: A Novel Particle-Based Iterative Scheme. - Giorgio Manganini; Matteo Pirotta; Marcello Restelli; Luigi Piroddi; Maria Prandini (IEEE Trans. Cybern., 2016)

Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems. - Carlo D'Eramo; Alessandro Nuara; Matteo Pirotta; Marcello Restelli (AAAI, 2017)

Unimodal Thompson Sampling for Graph-Structured Arms. - Stefano Paladino; Francesco Trovò; Marcello Restelli; Nicola Gatti 001 (AAAI, 2017)

Designing Learning Algorithms over the Sequence Form of an Extensive-Form Game. - Edoardo Manino; Nicola Gatti 001; Marcello Restelli (AAMAS, 2017)

Boosted Fitted Q-Iteration. - Samuele Tosatto; Matteo Pirotta; Carlo D'Eramo; Marcello Restelli (ICML, 2017)

Risk-averse trees for learning from logged bandit feedback. - Francesco Trovò; Stefano Paladino; Paolo Simone; Marcello Restelli; Nicola Gatti 001 (IJCNN, 2017)

User context estimation for public travel assistance and intelligent service scheduling. - Alessio Pagani; Francesco Bruschi; Vincenzo Rana; Marcello Restelli (ITSC, 2017)

Compatible Reward Inverse Reinforcement Learning. - Alberto Maria Metelli; Matteo Pirotta; Marcello Restelli (NIPS, 2017)

Adaptive Batch Size for Safe Policy Gradients. - Matteo Papini; Matteo Pirotta; Marcello Restelli (NIPS, 2017)

Exploiting structure and uncertainty of Bellman updates in Markov decision processes. - Davide Tateo; Carlo D'Eramo; Alessandro Nuara; Marcello Restelli; Andrea Bonarini (SSCI, 2017)

Gradient-based minimization for multi-expert Inverse Reinforcement Learning. - Davide Tateo; Matteo Pirotta; Marcello Restelli; Andrea Bonarini (SSCI, 2017)

Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games. - Lorenzo Bisi; Giuseppe De Nittis; Francesco Trovò; Marcello Restelli; Nicola Gatti 001 (UAI, 2017)

Cost-Sensitive Approach to Batch Size Adaptation for Gradient Descent. - Matteo Pirotta; Marcello Restelli (CoRR, 2017)

A Combinatorial-Bandit Algorithm for the Online Joint Bid/Budget Optimization of Pay-per-Click Advertising Campaigns. - Alessandro Nuara; Francesco Trovò; Nicola Gatti 001; Marcello Restelli (AAAI, 2018)

Configurable Markov Decision Processes. - Alberto Maria Metelli; Mirco Mutti; Marcello Restelli (ICML, 2018)

Stochastic Variance-Reduced Policy Gradient. - Matteo Papini; Damiano Binaghi; Giuseppe Canonaco; Matteo Pirotta; Marcello Restelli (ICML, 2018)

Importance Weighted Transfer of Samples in Reinforcement Learning. - Andrea Tirinzoni; Andrea Sessa; Matteo Pirotta; Marcello Restelli (ICML, 2018)

Targeting Optimization for Internet Advertising by Learning from Logged Bandit Feedback. - Margherita Gasparini; Alessandro Nuara; Francesco Trovò; Nicola Gatti 001; Marcello Restelli (IJCNN, 2018)

Does Reinforcement Learning outperform PID in the control of FES-induced elbow flex-extension? - Davide Di Febbo; Emilia Ambrosini; Matteo Pirotta; Eric Rojas 002; Marcello Restelli; Alessandra Laura Giulia Pedrocchi; Simona Ferrante (MeMeA, 2018)

Policy Optimization via Importance Sampling. - Alberto Maria Metelli; Matteo Papini; Francesco Faccio; Marcello Restelli (NeurIPS, 2018)

Transfer of Value Functions via Variational Methods. - Andrea Tirinzoni; Rafael Rodríguez-Sánchez 002; Marcello Restelli (NeurIPS, 2018)

Improving multi-armed bandit algorithms in online pricing settings. - Francesco Trovò; Stefano Paladino; Marcello Restelli; Nicola Gatti 001 (Int. J. Approx. Reason., 2018)

Reinforcement Learning in Configurable Continuous Environments. - Alberto Maria Metelli; Emanuele Ghelfi; Marcello Restelli (ICML, 2019)

Optimistic Policy Optimization via Multiple Importance Sampling. - Matteo Papini; Alberto Maria Metelli; Lorenzo Lupo; Marcello Restelli (ICML, 2019)

Transfer of Samples in Policy Search via Multiple Importance Sampling. - Andrea Tirinzoni; Mattia Salvini; Marcello Restelli (ICML, 2019)

Feature Selection via Mutual Information: New Theoretical Insights. - Mario Beraha; Alberto Maria Metelli; Matteo Papini; Andrea Tirinzoni; Marcello Restelli (IJCNN, 2019)

Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning. - Carlo D'Eramo; Andrea Cini; Marcello Restelli (IJCNN, 2019)

Exploration Driven by an Optimistic Bellman Equation. - Samuele Tosatto; Carlo D'Eramo; Joni Pajarinen; Marcello Restelli; Jan Peters 001 (IJCNN, 2019)

Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters. - Alberto Maria Metelli; Amarildo Likmeta; Marcello Restelli (NeurIPS, 2019)

Dealing with Interdependencies and Uncertainty in Multi-Channel Advertising Campaigns Optimization. - Alessandro Nuara; Nicola Sosio; Francesco Trovò; Maria Chiara Zaccardi; Nicola Gatti 001; Marcello Restelli (WWW, 2019)

Gradient-Aware Model-Based Policy Search. - Pierluca D'Oro; Alberto Maria Metelli; Andrea Tirinzoni; Matteo Papini; Marcello Restelli (AAAI, 2020)

An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies. - Mirco Mutti; Marcello Restelli (AAAI, 2020)

Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration. - Matteo Papini; Andrea Battistello; Marcello Restelli (AISTATS, 2020)

Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. - Giorgia Ramponi; Amarildo Likmeta; Alberto Maria Metelli; Andrea Tirinzoni; Marcello Restelli (AISTATS, 2020)

A Novel Confidence-Based Algorithm for Structured Bandits. - Andrea Tirinzoni; Alessandro Lazaric; Marcello Restelli (AISTATS, 2020)

Driving Exploration by Maximum Distribution in Gaussian Process Bandits. - Alessandro Nuara; Francesco Trovò; Dominic Crippa; Nicola Gatti 001; Marcello Restelli (AAMAS, 2020)

Model-Free Non-Stationarity Detection and Adaptation in Reinforcement Learning. - Giuseppe Canonaco; Marcello Restelli; Manuel Roveri (ECAI, 2020)

Foreign exchange trading: a risk-averse batch reinforcement learning approach. - Lorenzo Bisi; Pierre Liotet; Luca Sabbioni; Gianmarco Reho; Nico Montali; Marcello Restelli; Cristiana Corno (ICAIF, 2020)

Fast direct calibration of interest rate derivatives pricing models. - Luca Sabbioni; Marcello Restelli; Andrea Prampolini (ICAIF, 2020)

Dealing with transaction costs in portfolio optimization: online gradient descent with momentum. - Edoardo Vittori; Martino Bernasconi de Luca; Francesco Trovò; Marcello Restelli (ICAIF, 2020)

Option hedging with risk averse reinforcement learning. - Edoardo Vittori; Michele Trapletti; Marcello Restelli (ICAIF, 2020)

Sharing Knowledge in Multi-Task Deep Reinforcement Learning. - Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters 001 (ICLR, 2020)

Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning. - Alberto Maria Metelli; Flavio Mazzolini; Lorenzo Bisi; Luca Sabbioni; Marcello Restelli (ICML, 2020)

Sequential Transfer in Reinforcement Learning with a Generative Model. - Andrea Tirinzoni; Riccardo Poiani; Marcello Restelli (ICML, 2020)

Inferring Functional Properties from Fluid Dynamics Features. - Andrea Schillaci; Maurizio Quadrio; Carlotta Pipolo; Marcello Restelli; Giacomo Boracchi (ICPR, 2020)

Risk-Averse Trust Region Optimization for Reward-Volatility Reduction. - Lorenzo Bisi; Luca Sabbioni; Edoardo Vittori; Matteo Papini; Marcello Restelli (IJCAI, 2020)

Inverse Reinforcement Learning from a Gradient-based Learner. - Giorgia Ramponi; Gianluca Drappo; Marcello Restelli (NeurIPS, 2020)

An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits. - Andrea Tirinzoni; Matteo Pirotta; Marcello Restelli; Alessandro Lazaric (NeurIPS, 2020)

Time-Variant Variational Transfer for Value Functions. - Giuseppe Canonaco; Andrea Soprani; Manuel Roveri; Marcello Restelli (CoRR, 2020)

A Policy Gradient Method for Task-Agnostic Exploration. - Mirco Mutti; Lorenzo Pratissoli; Marcello Restelli (CoRR, 2020)

Newton-based Policy Optimization for Games. - Giorgia Ramponi; Marcello Restelli (CoRR, 2020)

On the use of the policy gradient and Hessian in inverse reinforcement learning. - Alberto Maria Metelli; Matteo Pirotta; Marcello Restelli (Intelligenza Artificiale, 2020)

Sliding-Window Thompson Sampling for Non-Stationary Settings. - Francesco Trovò; Marcello Restelli; Nicola Gatti 001 (J. Artif. Intell. Res., 2020)

Importance Sampling Techniques for Policy Optimization. - Alberto Maria Metelli; Matteo Papini; Nico Montali; Marcello Restelli (J. Mach. Learn. Res., 2020)

Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving. - Amarildo Likmeta; Alberto Maria Metelli; Andrea Tirinzoni; Riccardo Giol; Marcello Restelli; Danilo Romano (Robotics Auton. Syst., 2020)

Policy Optimization as Online Learning with Mediator Feedback. - Alberto Maria Metelli; Matteo Papini; Pierluca D'Oro; Marcello Restelli (AAAI, 2021)

Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate. - Mirco Mutti; Lorenzo Pratissoli; Marcello Restelli (AAAI, 2021)

Newton Optimization on Helmholtz Decomposition for Continuous Games. - Giorgia Ramponi; Marcello Restelli (AAAI, 2021)

Learning FX trading strategies with FQI and persistent actions. - Antonio Riva; Lorenzo Bisi; Pierre Liotet; Luca Sabbioni; Edoardo Vittori; Marco Pinciroli; Michele Trapletti; Marcello Restelli (ICAIF, 2021)

Monte carlo tree search for trading and hedging. - Edoardo Vittori; Amarildo Likmeta; Marcello Restelli (ICAIF, 2021)

Provably Efficient Learning of Transferable Rewards. - Alberto Maria Metelli; Giorgia Ramponi; Alessandro Concetti; Marcello Restelli (ICML, 2021)

Leveraging Good Representations in Linear Contextual Bandits. - Matteo Papini; Andrea Tirinzoni; Marcello Restelli; Alessandro Lazaric; Matteo Pirotta (ICML, 2021)

Meta-Reinforcement Learning by Tracking Task Non-stationarity. - Riccardo Poiani; Andrea Tirinzoni; Marcello Restelli (IJCAI, 2021)

Learning a Belief Representation for Delayed Reinforcement Learning. - Pierre Liotet; Erick Venneri; Marcello Restelli (IJCNN, 2021)

Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning. - Alberto Maria Metelli; Alessio Russo; Marcello Restelli (NeurIPS, 2021)

Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection. - Matteo Papini; Andrea Tirinzoni; Aldo Pacchiano; Marcello Restelli; Alessandro Lazaric; Matteo Pirotta (NeurIPS, 2021)

Learning in Non-Cooperative Configurable Markov Decision Processes. - Giorgia Ramponi; Alberto Maria Metelli; Alessandro Concetti; Marcello Restelli (NeurIPS, 2021)

Conservative Online Convex Optimization. - Martino Bernasconi de Luca; Edoardo Vittori; Francesco Trovò; Marcello Restelli (ECML/PKDD (1), 2021)

Exploiting History Data for Nonstationary Multi-armed Bandit. - Gerlando Re; Fabio Chiusano; Francesco Trovò; Diego Carrera; Giacomo Boracchi; Marcello Restelli (ECML/PKDD (1), 2021)

Time-variant variational transfer for value functions. - Giuseppe Canonaco; Andrea Soprani; Matteo Giuliani; Andrea Castelletti; Manuel Roveri; Marcello Restelli (UAI, 2021)

Gaussian Approximation for Bias Reduction in Q-Learning. - Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters 001; Marcello Restelli (J. Mach. Learn. Res., 2021)

MushroomRL: Simplifying Reinforcement Learning Research. - Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters 001 (J. Mach. Learn. Res., 2021)

Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach. - Alberto Maria Metelli; Matteo Pirotta; Daniele Calandriello; Marcello Restelli (J. Mach. Learn. Res., 2021)

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems. - Amarildo Likmeta; Alberto Maria Metelli; Giorgia Ramponi; Andrea Tirinzoni; Matteo Giuliani; Marcello Restelli (Mach. Learn., 2021)

Lifelong Hyper-Policy Optimization with Multiple Importance Sampling Regularization. - Pierre Liotet; Francesco Vidaich; Alberto Maria Metelli; Marcello Restelli (AAAI, 2022)

Unsupervised Reinforcement Learning in Multiple Environments. - Mirco Mutti; Mattia Mancassola; Marcello Restelli (AAAI, 2022)

Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning. - Khaled Eldowa; Lorenzo Bisi; Marcello Restelli (AISTATS, 2022)

Reward-Free Policy Space Compression for Reinforcement Learning. - Mirco Mutti; Stefano Del Col; Marcello Restelli (AISTATS, 2022)

Trust Region Meta Learning for Policy Optimization. - Manuel Occorso; Luca Sabbioni; Alberto Maria Metelli; Marcello Restelli (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach. - Martino Bernasconi; Stefano Martino; Edoardo Vittori; Francesco Trovò; Marcello Restelli (ICAIF, 2022)

Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts. - Antonio Riva; Lorenzo Bisi; Pierre Liotet; Luca Sabbioni; Edoardo Vittori; Marco Pinciroli; Michele Trapletti; Marcello Restelli (ICAIF, 2022)

Goal-Directed Planning via Hindsight Experience Replay. - Lorenzo Moro; Amarildo Likmeta; Enrico Prati; Marcello Restelli (ICLR, 2022)

Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning. - Angelo Damiani; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (ICML, 2022)

Delayed Reinforcement Learning by Imitation. - Pierre Liotet; Davide Maran; Lorenzo Bisi; Marcello Restelli (ICML, 2022)

Stochastic Rising Bandits. - Alberto Maria Metelli; Francesco Trovò; Matteo Pirola; Marcello Restelli (ICML, 2022)

The Importance of Non-Markovianity in Maximum State Entropy Exploration. - Mirco Mutti; Riccardo De Santi; Marcello Restelli (ICML, 2022)

Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts. - Giulia Romano; Andrea Agostini; Francesco Trovò; Nicola Gatti 001; Marcello Restelli (IJCAI, 2022)

Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse Management. - Julen Cestero; Marco Quartulli; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2022)

Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits. - Marco Mussi; Gianmarco Genalti; Francesco Trovò; Alessandro Nuara; Nicola Gatti 001; Marcello Restelli (KDD, 2022)

Off-Policy Evaluation with Deficient Support Using Side Information. - Nicolò Felicioni; Maurizio Ferrari Dacrema; Marcello Restelli; Paolo Cremonesi (NeurIPS, 2022)

Challenging Common Assumptions in Convex Reinforcement Learning. - Mirco Mutti; Riccardo De Santi; Piersilvio De Bartolomeis; Marcello Restelli (NeurIPS, 2022)

Multi-Fidelity Best-Arm Identification. - Riccardo Poiani; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2022)

Learning in Markov games: Can we exploit a general-sum opponent? - Giorgia Ramponi; Marcello Restelli (UAI, 2022)

A practical guide to multi-objective reinforcement learning and planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (Auton. Agents Multi Agent Syst., 2022)

Risk-averse policy optimization via risk-neutral policy optimization. - Lorenzo Bisi; Davide Santambrogio; Federico Sandrelli; Andrea Tirinzoni; Brian D. Ziebart; Marcello Restelli (Artif. Intell., 2022)

Online joint bid/daily budget optimization of Internet advertising campaigns. - Alessandro Nuara; Francesco Trovò; Nicola Gatti 001; Marcello Restelli (Artif. Intell., 2022)

Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review. - Sancho Salcedo-Sanz; Jorge Pérez-Aracil; Guido Ascenso; Javier Del Ser; David Casillas-Pérez; Christopher Kadow; Dusan Fister; David Barriopedro; Ricardo García-Herrera; Marcello Restelli; Matteo Giuliani; Andrea Castelletti (CoRR, 2022)

Policy space identification in configurable environments. - Alberto Maria Metelli; Guglielmo Manneschi; Marcello Restelli (Mach. Learn., 2022)

Smoothing policies and safe policy gradients. - Matteo Papini; Matteo Pirotta; Marcello Restelli (Mach. Learn., 2022)

Wasserstein Actor-Critic: Directed Exploration via Optimism for Continuous-Actions Control. - Amarildo Likmeta; Matteo Sacco; Alberto Maria Metelli; Marcello Restelli (AAAI, 2023)

Tight Performance Guarantees of Imitator Policies with Continuous Actions. - Davide Maran; Alberto Maria Metelli; Marcello Restelli (AAAI, 2023)

Dynamic Pricing with Volume Discounts in Online Settings. - Marco Mussi; Gianmarco Genalti; Alessandro Nuara; Francesco Trovò; Marcello Restelli; Nicola Gatti 001 (AAAI, 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 (AAAI, 2023)

Simultaneously Updating All Persistence Values in Reinforcement Learning. - Luca Sabbioni; Luca Al Daire; Lorenzo Bisi; Alberto Maria Metelli; Marcello Restelli (AAAI, 2023)

A Tale of Sampling and Estimation in Discounted Reinforcement Learning. - Alberto Maria Metelli; Mirco Mutti; Marcello Restelli (AISTATS, 2023)

A Brief Guide to Multi-Objective Reinforcement Learning and Planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (AAMAS, 2023)

Towards an AI-Based Framework for Autonomous Design and Construction: Learning from Reinforcement Learning Success in RTS Games. - Ahmed Elmaraghy; Jacopo Montali; Marcello Restelli; Francesco Causone; Pierpaolo Ruttico (CAAD Futures, 2023)

Towards Theoretical Understanding of Inverse Reinforcement Learning. - Alberto Maria Metelli; Filippo Lazzati; Marcello Restelli (ICML, 2023)

Dynamical Linear Bandits. - Marco Mussi; Alberto Maria Metelli; Marcello Restelli (ICML, 2023)

Truncating Trajectories in Monte Carlo Reinforcement Learning. - Riccardo Poiani; Alberto Maria Metelli; Marcello Restelli (ICML, 2023)

Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice. - Khaled Eldowa; Nicolò Cesa-Bianchi; Alberto Maria Metelli; Marcello Restelli (ITW, 2023)

Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach. - Riccardo Poiani; Nicole Nobili; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2023)

Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning. - Riccardo Zamboni; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2023)

Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes. - Luca Sabbioni; Francesco Corda; Marcello Restelli (ECML/PKDD (4), 2023)

On the Relation between Policy Improvement and Off-Policy Minimum-Variance Policy Evaluation. - Alberto Maria Metelli; Samuele Meta; Marcello Restelli (UAI, 2023)

An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-Markov Decision Processes. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Nonlinear Feature Aggregation: Two Algorithms driven by Theory. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Pure Exploration under Mediators' Feedback. - Riccardo Poiani; Alberto Maria Metelli; Marcello Restelli (CoRR, 2023)

Convex Reinforcement Learning in Finite Trials. - Mirco Mutti; Riccardo De Santi; Piersilvio De Bartolomeis; Marcello Restelli (J. Mach. Learn. Res., 2023)

An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (Trans. Mach. Learn. Res., 2023)

Risk-averse optimization of reward-based coherent risk measures. - Massimiliano Bonetti; Lorenzo Bisi; Marcello Restelli (Artif. Intell., 2023)

ARLO: A framework for Automated Reinforcement Learning. - Marco Mussi; Davide Lombarda; Alberto Maria Metelli; Francesco Trovò; Marcello Restelli (Expert Syst. Appl., 2023)

IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems. - Filippo Fedeli; Alberto Maria Metelli; Francesco Trovò; Marcello Restelli (IEEE Trans. Neural Networks Learn. Syst., 2023)

Online Markov Decision Processes Configuration with Continuous Decision Space. - Davide Maran; Pierriccardo Olivieri; Francesco Emanuele Stradi; Giuseppe Urso; Nicola Gatti 001; Marcello Restelli (AAAI, 2024)

Parameterized Projected Bellman Operator. - Théo Vincent; Alberto Maria Metelli; Boris Belousov; Jan Peters 001; Marcello Restelli; Carlo D'Eramo (AAAI, 2024)

Autoregressive Bandits. - Francesco Bacchiocchi; Gianmarco Genalti; Davide Maran; Marco Mussi; Marcello Restelli; Nicola Gatti 001; Alberto Maria Metelli (AISTATS, 2024)

Transfer Learning for Dynamical Systems Models via Autoencoders and GANs. - Angelo Damiani; Gustavo Viera-López; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (ACC, 2024)

Projection by Convolution: Optimal Sample Complexity for Reinforcement Learning in Continuous-Space MDPs. - Davide Maran; Alberto Maria Metelli; Matteo Papini; Marcello Restelli (COLT, 2024)

Building Surrogate Models Using Trajectories of Agents Trained by Reinforcement Learning. - Julen Cestero; Marco Quartulli; Marcello Restelli (ICANN (4), 2024)

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning. - Mirco Mutti; Riccardo De Santi; Marcello Restelli; Alexander Marx 001; Giorgia Ramponi (ICLR, 2024)

Graph-Triggered Rising Bandits. - Gianmarco Genalti; Marco Mussi; Nicola Gatti 001; Marcello Restelli; Matteo Castiglioni; Alberto Maria Metelli (ICML, 2024)

No-Regret Reinforcement Learning in Smooth MDPs. - Davide Maran; Alberto Maria Metelli; Matteo Papini; Marcello Restelli (ICML, 2024)

Factored-Reward Bandits with Intermediate Observations. - Marco Mussi; Simone Drago; Marcello Restelli; Alberto Maria Metelli (ICML, 2024)

Best Arm Identification for Stochastic Rising Bandits. - Marco Mussi; Alessandro Montenegro; Francesco Trovò; Marcello Restelli; Alberto Maria Metelli (ICML, 2024)

How to Explore with Belief: State Entropy Maximization in POMDPs. - Riccardo Zamboni; Duilio Cirino; Marcello Restelli; Mirco Mutti (ICML, 2024)

Causal Feature Selection via Transfer Entropy. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2024)

The Power of Hybrid Learning in Industrial Robotics: Efficient Grasping Strategies with Supervised-Driven Reinforcement Learning. - Vincenzo De Paola; Giuseppe Calcagno; Alberto Maria Metelli; Marcello Restelli (IJCNN, 2024)

A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. - Puze Liu; Jonas Günster; Niklas Funk; Simon Gröger; Dong Chen; Haitham Bou-Ammar; Julius Jankowski; Ante Maric; Sylvain Calinon; Andrej Orsula; Miguel S. Olivares-Méndez; Hongyi Zhou; et al. (NeurIPS, 2024)

Bandits with Ranking Feedback. - Davide Maran; Francesco Bacchiocchi; Francesco Emanuele Stradi; Matteo Castiglioni; Nicola Gatti 001; Marcello Restelli (NeurIPS, 2024)

Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs. - Davide Maran; Alberto Maria Metelli; Matteo Papini; Marcello Restelli (NeurIPS, 2024)

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning. - Riccardo Poiani; Gabriele Curti; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2024)

Optimal Multi-Fidelity Best-Arm Identification. - Riccardo Poiani; Rémy Degenne; Emilie Kaufmann; Alberto Maria Metelli; Marcello Restelli (NeurIPS, 2024)

Interpetable Target-Feature Aggregation for Multi-task Learning Based on Bias-Variance Analysis. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (ECML/PKDD (6), 2024)

A Provably Efficient Option-Based Algorithm for both High-Level and Low-Level Learning. - Gianluca Drappo; Alberto Maria Metelli; Marcello Restelli (RLJ, 2024)

Policy Gradient with Active Importance Sampling. - Matteo Papini; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (RLJ, 2024)

The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough. - Riccardo Zamboni; Duilio Cirino; Marcello Restelli; Mirco Mutti (RLJ, 2024)

Inverse Reinforcement Learning with Sub-optimal Experts. - Riccardo Poiani; Gabriele Curti; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Information Capacity Regret Bounds for Bandits with Mediator Feedback. - Khaled Eldowa; Nicolò Cesa-Bianchi; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

State and Action Factorization in Power Grids. - Gianvito Losapio; Davide Beretta; Marco Mussi; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting. - Gianmarco Genalti; Marco Mussi; Nicola Gatti 001; Marcello Restelli; Matteo Castiglioni; Alberto Maria Metelli (CoRR, 2024)

Efficient Learning of POMDPs with Known Observation Model in Average-Reward Setting. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2024)

Exploiting Risk-Aversion and Size-dependent fees in FX Trading with Fitted Natural Actor-Critic. - Vito Alessandro Monaco; Antonio Riva; Luca Sabbioni; Lorenzo Bisi; Edoardo Vittori; Marco Pinciroli; Michele Trapletti; Marcello Restelli (CoRR, 2024)

Statistical Analysis of Policy Space Compression Problem. - Majid Molaei; Marcello Restelli; Alberto Maria Metelli; Matteo Papini (CoRR, 2024)

A parametric algorithm is optimal for non-parametric regression of smooth functions. - Davide Maran; Marcello Restelli (CoRR, 2024)

Switching Latent Bandits. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (Trans. Mach. Learn. Res., 2024)

Optimizing Empty Container Repositioning and Fleet Deployment via Configurable Semi-POMDPs. - Riccardo Poiani; Ciprian Stirbu; Alberto Maria Metelli; Marcello Restelli (IEEE Trans. Intell. Transp. Syst., 2024)

Interpretable linear dimensionality reduction based on bias-variance analysis. - Paolo Bonetti; Alberto Maria Metelli; Marcello Restelli (Data Min. Knowl. Discov., 2024)

Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds. - Gabor Paczolay; Matteo Papini; Alberto Maria Metelli; István Á. Harmati; Marcello Restelli (Mach. Learn., 2024)

Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning. - Gianluca Drappo; Arnaud Robert; Marcello Restelli; Aldo A. Faisal; Alberto Maria Metelli; Ciara Pike-Burke (AISTATS, 2025)

Achieving $ widetilde{ mathcal{O}}( sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation Models. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (AISTATS, 2025)

Factored-reward bandits with intermediate observations: Regret minimization and best arm identification. - Marco Mussi; Simone Drago; Marcello Restelli; Alberto Maria Metelli (Artif. Intell., 2025)

Achieving O(√T) Regret in Average-Reward POMDPs with Known Observation Models. - Alessio Russo; Alberto Maria Metelli; Marcello Restelli (CoRR, 2025)

Towards Principled Multi-Agent Task Agnostic Exploration. - Riccardo Zamboni; Mirco Mutti; Marcello Restelli (CoRR, 2025)

Scalable Multi-Agent Offline Reinforcement Learning and the Role of Information. - Riccardo Zamboni; Enrico Brunetti; Marcello Restelli (CoRR, 2025)

Enhancing Diversity in Parallel Agents: A Maximum State Entropy Exploration Story. - Vincenzo De Paola; Riccardo Zamboni; Mirco Mutti; Marcello Restelli (CoRR, 2025)

A Reinforcement Learning Approach for Optimal Control in Microgrids. - Davide Salaorni; Federico Bianchi; Francesco Trovò; Marcello Restelli (CoRR, 2025)

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning. - Davide Salaorni; Vincenzo De Paola; Samuele Delpero; Giovanni Dispoto; Paolo Bonetti; Alessio Russo; Giuseppe Calcagno; Francesco Trovò; Matteo Papini; Alberto Maria Metelli; Marco Mussi; Marcello Restelli (CoRR, 2025)

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents. - Giovanni Dispoto; Paolo Bonetti; Marcello Restelli (CoRR, 2025)

Search or split: policy gradient with adaptive policy space. - Gianmarco Tedeschi; Matteo Papini; Alberto Maria Metelli; Marcello Restelli (Mach. Learn., 2025)