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Record W2144148590 · doi:10.1109/iat.2005.134

Towards an authority sharing based on the description logic action model

2005· article· en· W2144148590 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

VenueIEEE/WIC/ACM International Conference on Intelligent Agent Technology · 2005
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversité du Québec à Chicoutimi
FundersUniversité de Toulouse
KeywordsAutonomyComputer scienceTask (project management)Context (archaeology)Realization (probability)DilemmaAction (physics)Control (management)Human-in-the-loopKnowledge managementComputer securityHuman–computer interactionArtificial intelligencePolitical scienceEpistemologyLawEconomicsManagementMathematics

Abstract

fetched live from OpenAlex

Within the human in the loop context, the realization of a task is not only the accomplishment of human operator or the autonomous agent acting on his behalf but rather of both entities, and in which they have the same possibilities to propose, suspend, refuse, and stop each other. However, this cohabitation is both rich and complex, owing to the fact that the human and the agent are bound to not only agree on the various levels of realization of the task inside the same loop, but also to manage the autonomy - who controls who -. Hence, this gives rise to a dilemma between the autonomy of an agent that is useful but risky and the fallibility of human in control of the decision-making. The issue then is to work out a computational model of an agent authority sharing, for the purpose of dynamically and safely transferring decision-making control to the human user.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.236
GPT teacher head0.364
Teacher spread0.128 · 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