PIROTTA, MATTEO

PIROTTA, MATTEO  

DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA  

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Risultati 1 - 20 di 32 (tempo di esecuzione: 0.024 secondi).
Titolo Data di pubblicazione Autori File
A particle-based policy for the optimal control of Markov decision processes 1-gen-2014 PIROTTA, MATTEOMANGANINI, GIORGIOPIRODDI, LUIGIPRANDINI, MARIARESTELLI, MARCELLO
Adaptive Batch Size for Safe Policy Gradients 1-gen-2017 PAPINI, MATTEOM. PirottaM. Restelli
Adaptive step-size for policy gradient methods 1-gen-2014 PIROTTA, MATTEORESTELLI, MARCELLOBASCETTA, LUCA
An upper limb Functional Electrical Stimulation controller based on Reinforcement Learning: A feasibility case study. 1-gen-2018 D. Di FebboE. AmbrosiniM. PirottaM. RestelliA. PedrocchiS. Ferrante
Boosted Fitted Q-Iteration 1-gen-2017 TOSATTO, SAMUELEM. PirottaC. D'EramoM. Restelli
Compatible Reward Inverse Reinforcement Learning 1-gen-2017 METELLI, ALBERTO MARIAM. PirottaM. Restelli
Does Reinforcement Learning outperform PID in the control of FES-induced elbow flex-extension? 1-gen-2018 Di Febbo, DavideAmbrosini, EmiliaPirotta, MatteoRestelli, MarcelloPedrocchi, Alessandra L. G.Ferrante, Simona +
Estimating the maximum expected value in continuous reinforcement learning problems 1-gen-2017 D'Eramo, CarloNuara, AlessandroPirotta, MatteoRestelli, Marcello
Fitted policy search 1-gen-2011 MIGLIAVACCA, MARTINOPIROTTA, MATTEORESTELLI, MARCELLOBONARINI, ANDREA +
Fitted Policy Search: Direct Policy Search using a Batch Reinforcement Learning Approach 1-gen-2010 MIGLIAVACCA, MARTINOPIROTTA, MATTEORESTELLI, MARCELLOBONARINI, ANDREA +
Following Newton direction in Policy Gradient with parameter exploration 1-gen-2015 MANGANINI, GIORGIOPIROTTA, MATTEORESTELLI, MARCELLOBASCETTA, LUCA
Gaussian approximation for bias reduction in Q-learning 1-gen-2021 D'Eramo C.Nuara A.Pirotta M.Alippi C.Restelli M. +
Gradient-based minimization for multi-expert Inverse Reinforcement Learning 1-gen-2017 Davide TateoMatteo PirottaMarcello RestelliAndrea Bonarini
Importance Weighted Transfer of Samples in Reinforcement Learning 1-gen-2018 TIRINZONI, ANDREASESSA, ANDREAPirotta, MatteoRestelli, Marcello
Inverse Reinforcement Learning through Policy Gradient Minimization 1-gen-2016 PIROTTA, MATTEORESTELLI, MARCELLO
Leveraging Good Representations in Linear Contextual Bandits 1-gen-2021 Matteo PapiniAndrea TirinzoniMarcello RestelliAlessandro LazaricMatteo Pirotta
Multi-objective Reinforcement Learning through Continuous Pareto Manifold Approximation 1-gen-2016 PIROTTA, MATTEORESTELLI, MARCELLO +
Multi-objective reinforcement learning with continuous pareto frontier approximation 1-gen-2015 PIROTTA, MATTEORESTELLI, MARCELLO +
On the use of the policy gradient and Hessian in inverse reinforcement learning 1-gen-2020 Metelli A. M.Pirotta M.Restelli M.
Optimal control to reduce emissions in gasoline engines: An iterative learning control approach for ECU calibration maps improvement 1-gen-2015 CAPORALE, DANILODEORI, LUCAMURA, ROBERTOFALSONE, ALESSANDROVIGNALI, RICCARDO MARIAGIULIONI, LUCAPIROTTA, MATTEOMANGANINI, GIORGIO