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Record W1965168983 · doi:10.1109/aamas.2004.79

Building a Multi-Agent System for Automatic Negotiation in Web Service Applications

2004· article· en· W1965168983 on OpenAlex
Ambroise Ncho, Esma Aı̈meur

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

VenueAdaptive Agents and Multi-Agents Systems · 2004
Typearticle
Languageen
FieldComputer Science
TopicMulti-Agent Systems and Negotiation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsInteroperabilityThe InternetAutomationWeb serviceComputer scienceNegotiationContext (archaeology)World Wide WebService (business)Service-oriented architectureSoftware engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

Within the last decade, much effort has been put into the development of standards and technologies that enable the integration of Internet applications and the interoperability of Web services. The ultimate goal of these initiatives is to increase the automation of business processes. However many challenges remain to be addressed in order to reach a high-level of automation in Internet-based applications. Automatic negotiation is one of these challenges. In this paper we propose the Collaborative Agreement for Automatic Trading (CAAT), a Multi-Agent System framework that enables automatic negotiation in the context of a trading-based Web service.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.300
Teacher spread0.241 · 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