21 citations · 109 across the 23 of their papers we have counts for
28 papers
Proceedings 39th International Conference on Logic Programming
Enrico Pontelli, Stefania Costantini, Carmine Dodaro +7
This volume contains the Technical Communications presented at the 39th International Conference on Logic Programming (ICLP 2023), held at Imperial College London, UK from July 9 t…
Learning Reward Machines in Cooperative Multi-Agent Tasks
Leo Ardon, Daniel Furelos-Blanco, Alessandra Russo
This paper presents a novel approach to Multi-Agent Reinforcement Learning (MARL) that combines cooperative task decomposition with the learning of reward machines (RMs) encoding t…
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…
Numerical reasoning in machine reading comprehension tasks: are we there yet?
Hadeel Al-Negheimish, Pranava Madhyastha, Alessandra Russo
Numerical reasoning based machine reading comprehension is a task that involves reading comprehension along with using arithmetic operations such as addition, subtraction, sorting,…
FF-NSL: Feed-Forward Neural-Symbolic Learner
Daniel Cunnington, Mark Law, Alessandra Russo +1
Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified in a structured logical form. To ad…
pix2rule: End-to-end Neuro-symbolic Rule Learning
Nuri Cingillioglu, Alessandra Russo
Humans have the ability to seamlessly combine low-level visual input with high-level symbolic reasoning often in the form of recognising objects, learning relations between them an…