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Record W2912100673

Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems

2014· article· en· W2912100673 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsnot available
Fundersnot available
KeywordsVisionComputer scienceLibrary scienceOperations researchAutonomous agentTrack (disk drive)Artificial intelligenceEngineeringSociology
DOInot available

Abstract

fetched live from OpenAlex

The Autonomous Agents and MultiAgent Systems (AAMAS) conference series brings together researchers from around the world to share the latest advances in the field. It provides a highprofile and high-quality forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS 2002, the first of the series, was held in Bologna, followed by Melbourne (2003), New York (2004), Utrecht (2005), Hakodate (2006), Honolulu (2007), Estoril (2008), Budapest (2009), Toronto (2010), Taipei (2011), Valencia (2012), and Saint Paul (2013). This volume constitutes the proceedings of AAMAS 2014, the thirteenth conference in the series, held in Paris in May 2014. In line with previous editions, AAMAS 2014 attracted submissions for a general track and four special tracks: robotics, virtual agents, innovative applications, and a challenges and visions track. The special tracks were chaired by leaders in their corresponding fields: Noa Agmon and Luiz Chaimowicz chaired the robotics track, Elisabeth Andre and Sarit Kraus the virtual agents track, Tom Holvoet and Rajiv Maheswaran the innovative applications track, and Munindar Singh the challenges and visions track. The special track chairs worked with Program Committee Members (PC), Senior Program Committee (SPC) members, and the Program Chairs to select the papers submitted to the special tracks. Full paper (8 pages), challenges and vision (4 pages), and extended abstract (2 pages) submissions were solicited for AAMAS 2014. The papers were selected by means of a thorough review and discussion process, which included an opportunity for authors to respond to reviewer comments. All SPC members followed and contributed to the technical discussions on the papers they were overseeing and participated in a conference call with the program chairs, where each paper in their allocation was discussed. In addition to this, the special track chairs held conference calls with the program chairs to further discuss the papers in the special tracks. Full papers were presented orally in 20 minute slots; all full papers and extended abstracts were presented as posters during the conference. Out of the 709 submissions, 425 (60%) had a student as the primary author, 86 of these were accepted as full papers (12%), and a further 109 (15%) were accepted as extended abstracts.

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 score0.991
Threshold uncertainty score0.139

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 communication0.0000.000
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 head0.049
GPT teacher head0.280
Teacher spread0.231 · 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

Citations181
Published2014
Admission routes1
Has abstractyes

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