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Record W2109379881 · doi:10.1109/icmb.2007.14

An Intelligent Agent-Based Framework for Mobile Business

2007· article· en· W2109379881 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceMobile agentInteroperabilityScalabilityIntelligent agentStandardizationNegotiationMobile computingTask (project management)Mobile telephonySoftware agentMulti-agent systemComputer securityDistributed computingWorld Wide WebComputer networkDatabaseArtificial intelligenceMobile radioOperating systemEngineering

Abstract

fetched live from OpenAlex

This paper proposes a mobile, intelligent agent-based framework that allows buyers and sellers to perform business at remote locations. A business participant can generate a mobile, intelligent agent via a mobile device and dispatch the agent to the Internet to do business. The proposed framework brings in several advantages: First, it provides great convenience for traders as business can be conducted anytime and anywhere. Secondly, the user is freed from the time-consuming task of finding and negotiating with appropriate traders. Thirdly, it addresses the problem of limited and expensive connection time for mobile users: A trader can disconnect her mobile device from its server after launching a mobile agent. Later on, she can reconnect and call back the agent for results, therefore minimizing the connection time. Finally, by complying with the standardization body of FIPA, this flexible framework increases the interoperability between agent systems and provides high design scalability.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.615
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.023
GPT teacher head0.300
Teacher spread0.278 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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