research
∙
05/31/2022
Hierarchies of Reward Machines
Reward machines (RMs) are a recent formalism for representing the reward...
share
research
∙
05/25/2022
Inductive Learning of Complex Knowledge from Raw Data
One of the ultimate goals of Artificial Intelligence is to learn general...
research
∙
05/14/2022
Efficient lifting of symmetry breaking constraints for complex combinatorial problems
Many industrial applications require finding solutions to challenging co...
research
∙
06/24/2021
FF-NSL: Feed-Forward Neural-Symbolic Learner
Inductive Logic Programming (ILP) aims to learn generalised, interpretab...
research
∙
12/31/2020
Conflict-driven Inductive Logic Programming
The goal of Inductive Logic Programming (ILP) is to learn a program that...
research
∙
12/09/2020
NSL: Hybrid Interpretable Learning From Noisy Raw Data
Inductive Logic Programming (ILP) systems learn generalised, interpretab...
research
∙
09/08/2020
Induction and Exploitation of Subgoal Automata for Reinforcement Learning
In this paper we present ISA, an approach for learning and exploiting su...
research
∙
05/02/2020
The ILASP system for Inductive Learning of Answer Set Programs
The goal of Inductive Logic Programming (ILP) is to learn a program that...
research
∙
11/29/2019
Induction of Subgoal Automata for Reinforcement Learning
In this work we present ISA, a novel approach for learning and exploitin...
research
∙
06/23/2019
Inductive general game playing
General game playing (GGP) is a framework for evaluating an agent's gene...
research
∙
08/25/2018
Inductive Learning of Answer Set Programs from Noisy Examples
In recent years, non-monotonic Inductive Logic Programming has received ...
research
∙
08/05/2016
