|
Descripción
|
|
|---|---|
| We present our work on the training of robotised architec- tural components of intelligent buildings, focusing on main architectural components and features such as fac ?ades, roofs and partitions. The pa- rameters governing such components may be either quantitative (such as temperature, humidity, configuration of the elements) or qualitative (such as ergonomics and aesthetics), which cannot easily be described by mathematical parameters. Due to their complexity, it is often impos- sible -or at least impractical, to hardcode suitable controllers for such robotised structures. Thus, we propose the use of Artificial Intelligence learning techniques, concretely Evolutionary Algorithms, so that the user can teach the robotised components how to behave in response to chang- ing environmental conditions or user preferences. This idea is tested on an intelligent rooftop with variable geometry, that learns optimal config- urations with respect to ambient light during training sessions. | |
|
Internacional
|
Si |
|
Nombre congreso
|
18th European Conference on the Applications of Evolutionary Computation |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
|
|
Revisores
|
Si |
|
ISBN o ISSN
|
|
|
DOI
|
|
|
Fecha inicio congreso
|
08/04/2015 |
|
Fecha fin congreso
|
10/04/2015 |
|
Desde la página
|
|
|
Hasta la página
|
|
|
Título de las actas
|
|