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Record W30608750 · doi:10.5281/zenodo.1179526

An Agent-Based System For Robotic Musical Performance

2008· article· en· W30608750 on OpenAlex
Arne Eigenfeldt, Ajay Kapur

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

VenueNew Interfaces for Musical Expression · 2008
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer sciencePolyphonyImprovisationSoftware agentSoftwareHuman–computer interactionMusicalGestureRobotMulti-agent systemIntelligent agentArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

This paper presents an agent-based architecture for robotic musical instruments that generate polyphonic rhythmic patterns that continuously evolve and develop in a musically "intelligent" manner. Agent-based software offers a new method for real-time composition that allows for complex interactions between individual voices while requiring very little user interaction or supervision. The system described, Kinetic Engine, is an environment in which individual software agents, emulate drummers improvising within a percussion ensemble. Player agents assume roles and personalities within the ensemble, and communicate with one another to create complex rhythmic interactions. In this project, the ensemble is comprised of a 12-armed musical robot, MahaDeviBot, in which each limb has its own software agent controlling what it performs.

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: Empirical · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score0.769

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.270
Teacher spread0.233 · 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