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Record W2082226636 · doi:10.2495/arc080121

Swarm-driven idea models – from insect nests to modern architecture

2008· article· en· W2082226636 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWIT transactions on ecology and the environment · 2008
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSwarm behaviourComputer scienceArchitectureBlueprintArtificial intelligenceSwarm intelligenceTheoretical computer scienceParticle swarm optimizationSoftware engineeringEngineeringMachine learningGeography

Abstract

fetched live from OpenAlex

Inspired by the construction behavior of social insects we have developed a computational model of a swarm to build architectural idea models in virtual three-dimensional space. Instead of following a blueprint for construction, the individuals of a swarm react to their local environment according to an innate behavioral script. Through the interplay of the swarm with its environment, interaction sequences take place that give rise to complex emergent constructions. The configuration of the swarm determines the character of the emerging architectural models. We breed swarms that meet our expectations through artificial evolution, a very general framework for computationally phrased optimization problems. We present several evolved, swarm-built architectural idea models and discuss their potential in regards to modern ecological architecture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.666
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.161
Teacher spread0.151 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it