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  4. Efficient Light Source Placement using Quantum Computing
 
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2023
Conference Paper
Title

Efficient Light Source Placement using Quantum Computing

Abstract
NP-hard problems regularly come up in video games, with interesting connections to real-world problems. In the game Minecraft, players place torches on the ground to light up dark areas. Placing them in a way that minimizes the total number of torches to save resources is far from trivial. In this paper, we use Quantum Computing to approach this problem. To this end, we derive a QUBO formulation of the torch placement problem, which we uncover to be very similar to another NP-hard problem. We employ a solution strategy that involves learning Lagrangian weights in an iterative process, adding to the ever growing toolbox of QUBO formulations. Finally, we perform experiments on real quantum hardware using real game data to demonstrate that our approach yields good torch placements.
Author(s)
Mücke, Sascha
Technische Universität Dortmund
Gerlach, Thore Thassilo
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Mainwork
LWDA 2023, Lernen, Wissen, Daten, Analysen. Conference Proceedings  
Project(s)
The Lamarr Institute for Machine Learning and Artificial Intelligence  
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Conference
Lernen, Wissen, Daten, Analysen Conference 2023  
Open Access
File(s)
Download (2.99 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.24406/publica-2792
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • ADMM

  • Constrained Optimization

  • Minecraft

  • Quantum Computing

  • QUBO

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