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20182022
most citedEfficient lifting of symmetry breaking constraints for complex combinatorial problems

2 citations · 2 across the 1 of their papers we have counts for

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cs.AI20222 cited

Efficient lifting of symmetry breaking constraints for complex combinatorial problems

Alice Tarzariol, Martin Gebser, Mark Law +1

Many industrial applications require finding solutions to challenging combinatorial problems. Efficient elimination of symmetric solution candidates is one of the key enablers for…

cs.AI2020

Induction and Exploitation of Subgoal Automata for Reinforcement Learning

Daniel Furelos-Blanco, Mark Law, Anders Jonsson +2

In this paper we present ISA, an approach for learning and exploiting subgoals in episodic reinforcement learning (RL) tasks. ISA interleaves reinforcement learning with the induct…

cs.AI2020

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…

cs.AI2019

Inductive general game playing

Andrew Cropper, Richard Evans, Mark Law

General game playing (GGP) is a framework for evaluating an agent's general intelligence across a wide range of tasks. In the GGP competition, an agent is given the rules of a game…

cs.AI2018

Inductive Learning of Answer Set Programs from Noisy Examples

Mark Law, Alessandra Russo, Krysia Broda

In recent years, non-monotonic Inductive Logic Programming has received growing interest. Specifically, several new learning frameworks and algorithms have been introduced for lear…