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Record W92854860

PLAMAGS: a language and environment to specify intelligent agents in virtual geo-referenced worlds

2008· article· en· W92854860 on OpenAlex
Tony Garneau, Bernard Moulin, Sylvain Delisle

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

Venueinternational conference on Modelling and simulation · 2008
Typearticle
Languageen
FieldEngineering
TopicEvacuation and Crowd Dynamics
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité Laval
Fundersnot available
KeywordsComputer sciencePopularityHuman–computer interactionVisualizationField (mathematics)Software engineeringPerceptionVirtual machineProgramming languageArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The micro-simulation of social and urban phenomena using software agents in geo-referenced virtual environments is a field of research whose popularity has strongly grown recently. Several platforms were developed for the specification and the implementation of this type of simulations, but they do not yet offer a complete language for the specification and validation of agents' behaviors which have apprehension capacities of virtual space (perception, reasoning on their objectives, etc). In this article we present the PLAMAGS project in which we propose an agent-oriented language, a development environment and a 3D visualization engine completely dedicated to the development and the execution of multi-agent geo-simulations.

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: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.467

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 head0.080
GPT teacher head0.298
Teacher spread0.218 · 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