Designer-driven 3D buildings generated using variable neighborhood search

This paper presents a mechanism to generate virtual buildings considering designer constraints and guidelines. This mechanism is implemented as a pipeline of different Variable Neighborhood Search (VNS) optimization processes in which several subproblems are tackled (1) rooms locations, (2) connectivity graph, and (3) element placement. The core VNS algorithm includes some variants to improve its performance, such as, for example constraint handling and biased operator selection. The optimization process uses a toolkit of construction primitives implemented as "smart objects" providing basic elements such as rooms, doors, staircases and other connectors. The paper also shows experimental results of the application of different designer constraints to a wide range of buildings from small houses to a large castle with several underground levels

An Integrated Framework for AI Assisted Level Design in 2D Platformers

The design of video game levels is a complex and critical task. Levels need to elicit fun and challenge while avoiding frustration at all costs. In this paper, we present a framework to assist designers in the creation of levels for 2D platformers. Our framework provides designers with a toolbox (i) to create 2D platformer levels, (ii) to estimate the difficulty and probability of success of single jump actions (the main mechanics of platformer games), and (iii) a set of metrics to evaluate the difficulty and probability of completion of entire levels. At the end, we present the results of a set of experiments we carried out with human players to validate the metrics included in our framework.Comment: Submitted to the IEEE Game Entertainment and Media Conference 201

BIMBOT (Inteligencia artificial aplicada al diseño con BIM)

[EN] BIMBOT is an intelligent design assistant for AEC industry. Its toolset runs on a BIM modelling software and produces a series of design solutions through optimised BIM models. It works with the use of advanced artificial intelligence (AI) methods (soft computing optimisation and machine learning) and supported by NoSQL databases. BIMBOT works in several stages:First, the definition of constraints/priorities established by the user runs a generative design process boosted by several AI methods. It creates different solutions on BIM models stored and refined from a catalogue of intelligent objects. So, an interactive process begins in which the users may import BIM models with proposed designs, create or edit them on-the-fly and get assisted by a series of configurable metrics that drive the quality of the design according to the initial preferences. So, we get a complete BIM project as a result of the iterative process. Finally, the continuous training of the algorithms will improve the efficiency in future designs.BIMBOT is conceived to extend the skills designers through software development BIM allowing them to be more productive in complex tasks in their design process.BIMBOT is funded by the European Eureka/Eurostars program (E!12863).[ES] BIMBOT es un asistente de diseño inteligente para la industria AEC. Sus herramientas se ejecutan sobre un software de modelado BIM y producen varias soluciones de diseño con modelos BIM optimizados. Funciona con el uso de métodos avanzados de Inteligencia Artificial (optimización soft computing y Machine Learning) y es compatible con bases de datos NoSQL. Contempla varias etapas:  La definición por el usuario de restricciones / prioridades establecidas ejecuta un proceso de diseño generativo impulsado por varios métodos de IA. Éste crea diferentes soluciones en modelos BIM almacenados y refinados a partir de un catálogo de objetos inteligentes. Con ello, los usuarios pueden interactuar importando modelos BIM con diseños propuestos, crearlos o editarlos in situ y recibir asistencia de una serie de métricas configurables que dan calidad al diseño de acuerdo con las preferencias iniciales. Así, obtenemos un Modelo BIM completo como resultado del proceso iterativo. Finalmente, el entrenamiento continuo de los algoritmos mejorará la eficiencia en futuros diseños. BIMBOT está concebido para extender las habilidades de los diseñadores a través del desarrollo de software BIM, permitiéndoles ser más productivos en tareas complejas del proceso de diseño. BIMBOT está financiado por el programa europeo Eureka / Eurostars (E! 12863).BIMBOT is funded by the European Eureka/Eurostars program (E!12863)Frías, C.; Peña, JM.; Sánchez, É.; Almeida, L. (2020). BIMBOT-(Artificial intelligence applied to BIM design). EGE Revista de Expresión Gráfica en la Edificación. 0(12):45-60. https://doi.org/10.4995/ege.2020.13942OJS456001

Designer-driven 3D buildings generated using Variable Neighborhood Search

This paper presents a mechanism to generate virtual buildings considering designer constraints and guidelines. This mechanism is implemented as a pipeline of different Variable Neighborhood Search (VNS) optimization processes in which several subproblems are tackled (1) rooms locations, (2) connectivity graph, and (3) element placement. The core VNS algorithm includes some variants to improve its performance, such as, for example constraint handling and biased operator selection. The optimization process uses a toolkit of construction primitives implemented as "smart objects" providing basic elements such as rooms, doors, staircases and other connectors. The paper also shows experimental results of the application of different designer constraints to a wide range of buildings from small houses to a large castle with several underground levels. Document type: Conference objec