Design with shape grammars and reinforcement learning

  • Authors:
  • Manuela Ruiz-Montiel;Javier Boned;Juan Gavilanes;Eduardo JiméNez;Lawrence Mandow;José-Luis PéRez-De-La-Cruz

  • Affiliations:
  • Escuela Técnica Superior de Ingenierıa Informática, Bulevar Louis Pasteur, No. 35, Campus de Teatinos, Universidad de Málaga, 29071 Málaga, Spain;Escuela Técnica Superior de Arquitectura, Campus de El Ejido, Universidad de Málaga, 29071 Málaga, Spain;Escuela Técnica Superior de Arquitectura, Campus de El Ejido, Universidad de Málaga, 29071 Málaga, Spain;Escuela Técnica Superior de Arquitectura, Campus de El Ejido, Universidad de Málaga, 29071 Málaga, Spain;Escuela Técnica Superior de Ingenierıa Informática, Bulevar Louis Pasteur, No. 35, Campus de Teatinos, Universidad de Málaga, 29071 Málaga, Spain;Escuela Técnica Superior de Ingenierıa Informática, Bulevar Louis Pasteur, No. 35, Campus de Teatinos, Universidad de Málaga, 29071 Málaga, Spain

  • Venue:
  • Advanced Engineering Informatics
  • Year:
  • 2013

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Abstract

Shape grammars are a powerful and appealing formalism for automatic shape generation in computer-based design systems. This paper presents a proposal complementing the generative power of shape grammars with reinforcement learning techniques. We use simple (naive) shape grammars capable of generating a large variety of different designs. In order to generate those designs that comply with given design requirements, the grammar is subject to a process of machine learning using reinforcement learning techniques. Based on this method, we have developed a system for architectural design, aimed at generating two-dimensional layout schemes of single-family housing units. Using relatively simple grammar rules, we learn to generate schemes that satisfy a set of requirements stated in a design guideline. Obtained results are presented and discussed.