Mirco Mutti | DeepAI

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Featured Co-authors

Marcello Restelli
59 publications
Michael Bronstein
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Matteo Castiglioni
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Alberto Marchesi
32 publications
Alberto Maria Metelli
26 publications
Emanuele Rossi
11 publications
Martino Bernasconi
6 publications
Riccardo De Santi
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Piersilvio De Bartolomeis
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Lorenzo Pratissoli
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Stefano Del Col
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∙ 06/21/2023

Persuading Farsighted Receivers in MDPs: the Power of Honesty

Bayesian persuasion studies the problem faced by an informed sender who ...

0 Martino Bernasconi, et al. ∙

∙ 04/11/2023

A Tale of Sampling and Estimation in Discounted Reinforcement Learning

The most relevant problems in discounted reinforcement learning involve ...

0 Alberto Maria Metelli, et al. ∙

∙ 02/22/2022

Reward-Free Policy Space Compression for Reinforcement Learning

In reinforcement learning, we encode the potential behaviors of an agent...

0 Mirco Mutti, et al. ∙

∙ 02/14/2022

Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization

In the sequential decision making setting, an agent aims to achieve syst...

0 Mirco Mutti, et al. ∙

∙ 02/07/2022

The Importance of Non-Markovianity in Maximum State Entropy Exploration

In the maximum state entropy exploration framework, an agent interacts w...

0 Mirco Mutti, et al. ∙

∙ 02/03/2022

Challenging Common Assumptions in Convex Reinforcement Learning

The classic Reinforcement Learning (RL) formulation concerns the maximiz...

6 Mirco Mutti, et al. ∙

∙ 12/16/2021

Unsupervised Reinforcement Learning in Multiple Environments

Several recent works have been dedicated to unsupervised reinforcement l...

0 Mirco Mutti, et al. ∙

∙ 07/09/2020

A Policy Gradient Method for Task-Agnostic Exploration

In a reward-free environment, what is a suitable intrinsic objective for...

0 Mirco Mutti, et al. ∙

∙ 07/10/2019

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

What is a good exploration strategy for an agent that interacts with an ...

0 Mirco Mutti, et al. ∙

∙ 06/14/2018

Configurable Markov Decision Processes

In many real-world problems, there is the possibility to configure, to a...

0 Alberto Maria Metelli, et al. ∙

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