21 citations · 60 across the 9 of their papers we have counts for
3 papers · 1 filter
Hierarchies of Reward Machines
Daniel Furelos-Blanco, Mark Law, Anders Jonsson +2
Reward machines (RMs) are a recent formalism for representing the reward function of a reinforcement learning task through a finite-state machine whose edges encode subgoals of the…
Induction of Subgoal Automata for Reinforcement Learning
Daniel Furelos-Blanco, Mark Law, Alessandra Russo +2
In this work we present ISA, a novel approach for learning and exploiting subgoals in reinforcement learning (RL). Our method relies on inducing an automaton whose transitions are…
Saliency Maps Generation for Automatic Text Summarization
David Tuckey, Krysia Broda, Alessandra Russo
Saliency map generation techniques are at the forefront of explainable AI literature for a broad range of machine learning applications. Our goal is to question the limits of these…