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Record W2026145294 · doi:10.2991/icmt-13.2013.71

Integrating Multiagent Systems into Virtual Worlds

2013· article· en· W2026145294 on OpenAlexaff
Grant McClure, Virwaney Sandeep, Fuhua Lin

Bibliographic record

VenueAdvances in intelligent systems research/Advances in Intelligent Systems Research · 2013
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsAthabasca University
Fundersnot available
KeywordsComputer scienceMetaverseMulti-agent systemHuman–computer interactionVirtual agentVirtual realityArtificial intelligence

Abstract

fetched live from OpenAlex

Abstr act. Incorporating autonomy and intelligence into virtual worlds to build an engaging virtual environment for applications such as serious games is becoming more desirable. There are challenges in integrating these systems including concerns with synchronization, communication, monitoring, efficiency, and control. This paper presents an approach to integrating a virtual world engine with a multiagent system platform through the creation of an interface between them. We show the feasibility and effectiveness of the approach through developing agents controlled non-player controlled characters (NPCs) in Open Wonderland and purposeful communication channels among agents using Jason AgentSpeak.

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.

How this classification was reachedexpand

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)0.029
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0080.010
Science and technology studies0.0020.001
Scholarly communication0.0040.009
Open science0.0080.003
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.004

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 head0.087
GPT teacher head0.425
Teacher spread0.338 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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