Authors:
Johannes Bayer
;
Syed Saqib Bukhari
and
Andreas Dengel
Affiliation:
German Research Center for Artificial Intelligence, Germany
Keyword(s):
Archistant, Archistant WebUI, LSTM, Early Design Phases, Architectural Support.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Data Engineering
;
Graphical and Graph-Based Models
;
Information Retrieval
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Shape Representation
;
Software Engineering
;
Theory and Methods
;
Web Applications
Abstract:
While computerized tools for late design phases are well-established in the architectural domain, early design
phases still lack widespread, automated solutions. During these phases, the actual concept of a building is
developed in a creative process which is conducted manually nowadays. In this paper, we present a novel
strategy that tackles the problem in a semi-automated way, where long short-term memories (LSTMs) are
making suggestions for each design step based on the user’s existing concept. A design step could be for
example the creation of connections between rooms given a list of rooms or the creation of room layouts given
a graph of connected rooms. This results in a tightly interleaved interaction between the user and the LSTMs.
We propose two approaches for creating LSTMs with this behavior. In the first approach, one LSTM is trained
for each design step. In the other approach, suggestions for all design steps are made by a single LSTM.
We evaluate these approaches agains
t each other by testing their performance on a set of floor plans. Finally,
we present the integration of the best performing approach in an existing sketching software, resulting in an
auto-completion for floor plans, similar to text auto-completion in modern office software.
(More)