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Record W1983933909 · doi:10.1109/wi-iat.2012.255

A Multi Scale Cognitive Architecture to Account for the Adaptive and Reflective Nature of Behaviour

2012· article· en· W1983933909 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

Venue2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology · 2012
Typearticle
Languageen
FieldComputer Science
TopicCognitive Science and Mapping
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceCognitive architectureArchitectureCognitionContext (archaeology)Situational ethicsAdaptive behaviorScale (ratio)Cognitive systemsHuman–computer interactionCognitive modelArtificial intelligenceTrough (economics)Cognitive sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

We present a multi-agent cognitive architecture in which reactive and sequential processes can dynamically influence each other to insure that behaviour is responsive to current context (behavioural and situational) while sensitive to the longer term behavioural sequences needed to solve complex problems. We present the implementation of such a system using an agent based approach and illustrate its processing trough the simulation of two psychological tasks.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.065
GPT teacher head0.346
Teacher spread0.281 · 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