1 code implementation • ICLR 2020 • Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
We study the benefit of sharing representations among tasks to enable the effective use of deep neural networks in Multi-Task Reinforcement Learning.
1 code implementation • 21 Jun 2022 • Davide Tateo, Davide Antonio Cucci, Matteo Matteucci, Andrea Bonarini
In this paper, we propose the use of an efficient representation, based on structural points, for the geometry of objects to be used as landmarks in a monocular semantic SLAM system based on the pose-graph formulation.
no code implementations • 22 Feb 2021 • Mirza Ramicic, Andrea Bonarini
Faced with an ever-increasing complexity of their domains of application, artificial learning agents are now able to scale up in their ability to process an overwhelming amount of information coming from their interaction with an environment.
2 code implementations • 4 Jan 2020 • Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MushroomRL is an open-source Python library developed to simplify the process of implementing and running Reinforcement Learning (RL) experiments.
no code implementations • 29 Dec 2019 • Mirza Ramicic, Andrea Bonarini
Online reinforcement learning agents are currently able to process an increasing amount of data by converting it into a higher order value functions.