21 citations · 27 across the 4 of their papers we have counts for
4 papers
Predicting and Understanding Human Action Decisions during Skillful Joint-Action via Machine Learning and Explainable-AI
Fabrizia Auletta, Rachel W. Kallen, Mario di Bernardo +1
This study uses supervised machine learning (SML) and explainable artificial intelligence (AI) to model, predict and understand human decision-making during skillful joint-action.…
Herding stochastic autonomous agents via local control rules and online global target selection strategies
Fabrizia Auletta, Davide Fiore, Michael J. Richardson +1
In this Paper we propose a simple yet effective set of local control rules to make a group of "herder agents" collect and contain in a desired region an ensemble of non-cooperative…
Control-Tutored Reinforcement Learning
Francesco De Lellis, Fabrizia Auletta, Giovanni Russo +2
We introduce a control-tutored reinforcement learning (CTRL) algorithm. The idea is to enhance tabular learning algorithms so as to improve the exploration of the state-space, and…
Control-Tutored Reinforcement Learning: an application to the Herding Problem
Francesco De Lellis, Fabrizia Auletta, Giovanni Russo +1
In this extended abstract we introduce a novel control-tutored Q-learning approach (CTQL) as part of the ongoing effort in developing model-based and safe RL for continuous state s…