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Record W2105536731 · doi:10.1109/waina.2011.15

An Approach for Integrating 3D Virtual Worlds with Multiagent Systems

2011· article· en· W2105536731 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsAthabasca University
Fundersnot available
KeywordsMetaverseJADE (particle detector)Computer scienceMulti-agent systemThe InternetTUTORVirtual realityHuman–computer interactionInstructional simulationVirtual learning environmentMultimediaWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Education is incorporating more and more of the capabilities provided by the Internet. One such move is the incorporation of 3D virtual worlds in the learning environment. Another is the increasing development of multiagent systems that support the learner or the tutor. Integrating pedagogically based multiagent systems with 3D virtual worlds could provide a more engaging immersive learning environment. This paper explores the feasibility of integrating a 3D virtual world with a pedagogical multiagent system named QuizMASter, an educational game for elearning that helps students learn their course material through friendly competition. The integration was developed by devising, implementing and testing an approach using open source technologies, namely, Open Wonderland and JADE. The result is encouraging as the integration is technically feasible, not overly difficult and opens a door to further integration opportunities.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.376

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 communication0.0000.001
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 head0.053
GPT teacher head0.250
Teacher spread0.197 · 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

Quick stats

Citations18
Published2011
Admission routes1
Has abstractyes

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