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Record W2188156513

Symbol Recognition and Artificial Emotion for Making an Autonomoius Robot Attend the AAAI Conference.

2000· article· en· W2188156513 on OpenAlexaff
François Michaud, Dominic Létourneau, Jonathan Audet, François Bélanger

Bibliographic record

VenueNational Conference on Artificial Intelligence · 2000
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsRobotComputer scienceHuman–computer interactionMobile robotsortArtificial intelligenceCompassPentiumSocial robotFrame (networking)Robot controlComputer vision
DOInot available

Abstract

fetched live from OpenAlex

LABORIUS is a young research laboratory interested in designing autonomous systems that can assist human in real life tasks. To do so, robots require some sort of “social intelligence”, giving them the ability to interact with various types of agents (humans, animals, robots and other physical agents). Our team of robots is made of six Pioneer 2 robots, three indoor and three outdoor models, with each robot equipped with 16 sonars, a compass, a gripper, a camera with a frame grabber and a Fast Track Vision System, a RF Ethernet-modem connection and a Pentium 233 MHz PC-104 onboard computer. The programming environment used is Ayllu (Werger 2000), a tool for development of behavior-based control systems for intelligent mobile robots.

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.

How this classification was reachedexpand

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.275
GPT teacher head0.367
Teacher spread0.092 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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