1 citations · 1 across the 3 of their papers we have counts for
6 papers
The ILASP system for Inductive Learning of Answer Set Programs
Mark Law, Alessandra Russo, Krysia Broda
The goal of Inductive Logic Programming (ILP) is to learn a program that explains a set of examples in the context of some pre-existing background knowledge. Until recently, most r…
A general framework for scientifically inspired explanations in AI
David Tuckey, Alessandra Russo, Krysia Broda
Explainability in AI is gaining attention in the computer science community in response to the increasing success of deep learning and the important need of justifying how such sys…
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…
Towards Intuitive Reasoning in Axiomatic Geometry
Maximilian Doré, Krysia Broda
Proving lemmas in synthetic geometry is often a time-consuming endeavour since many intermediate lemmas need to be proven before interesting results can be obtained. Improvements i…
The Elfe System - Verifying mathematical proofs of undergraduate students
Maximilian Doré, Krysia Broda
Elfe is an interactive system for teaching basic proof methods in discrete mathematics. The user inputs a mathematical text written in fair English which is converted to a special…