An Integrated Architecture for Multiagent Virtual Worlds for Performing Adaptive Testing Games.
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.
Bibliographic record
Abstract
One of the key success factors that contribute towards the creation and sustenance of online (2D and 3D) virtual worlds for learning might be to provide game-style educational activities. However, there is no development platform available which can meet the inherent system requirements including usability of platform and scalability to modern massively multiplayer online games, yet focused on engaging learning for the individual user. Work has been done with software agents in the context of multiagent systems (MAS), and it makes sense to try to leverage that work when it comes to modeling functional modules, controlling realistic non-player characters (NPCs), and Personal Assistants for Learning (PALs) in a virtual learning world. There are challenges to integrating a multi-agent system into a virtual world including concerns with synchronization, communication, monitoring, efficiency, and control. This paper describes the design and implementation of an integrated architecture for performing and facilitating quiz games for adaptive testing with a multi-agent system JADE/Jason and a 3D virtual world engine Open Wonderland.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it