most citedMushroomRL: Simplifying Reinforcement Learning Research

35 citations · 43 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG20203 cited

Sequential Transfer in Reinforcement Learning with a Generative Model

Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli

We are interested in how to design reinforcement learning agents that provably reduce the sample complexity for learning new tasks by transferring knowledge from previously-solved…

cs.LG2020

Time-Variant Variational Transfer for Value Functions

Giuseppe Canonaco, Andrea Soprani, Manuel Roveri +1

In most of the transfer learning approaches to reinforcement learning (RL) the distribution over the tasks is assumed to be stationary. Therefore, the target and source tasks are i…

cs.LG20201 cited

A Novel Confidence-Based Algorithm for Structured Bandits

Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli

We study finite-armed stochastic bandits where the rewards of each arm might be correlated to those of other arms. We introduce a novel phased algorithm that exploits the given str…

cs.LG20201 cited

Online Joint Bid/Daily Budget Optimization of Internet Advertising Campaigns

Alessandro Nuara, Francesco Trovò, Nicola Gatti +1

Pay-per-click advertising includes various formats (\emph{e.g.}, search, contextual, social) with a total investment of more than 200 billion USD per year worldwide. An advertiser…

cs.LG202035 cited

MushroomRL: Simplifying Reinforcement Learning Research

Carlo D'Eramo, Davide Tateo, Andrea Bonarini +2

MushroomRL is an open-source Python library developed to simplify the process of implementing and running Reinforcement Learning (RL) experiments. Compared to other available libra…

cs.AI20143 cited

Multi-objective Reinforcement Learning with Continuous Pareto Frontier Approximation Supplementary Material

Matteo Pirotta, Simone Parisi, Marcello Restelli

This document contains supplementary material for the paper "Multi-objective Reinforcement Learning with Continuous Pareto Frontier Approximation", published at the Twenty-Ninth AA…