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Arithmetic Billiard Paths Revisited: Escaping from a Rectangular Room

2023· article· en· W4386597136 on OpenAlexaff
Somnath Kundu, Yeganeh Bahoo, Onur Çağırıcı, Steven M. LaValle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsToronto Metropolitan University
FundersAcademy of Finland
KeywordsRobotRectangleDynamical billiardsPoint (geometry)Line (geometry)Computer scienceReflection (computer programming)MathematicsGeometryAlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

In this work, we consider a problem where a robot can move in a straight line inside a 2D rectangular room with integer lengths until it hits any part of the wall of the room. If the robot hits any part of a wall other than the corners or any point of an opening, then the robot bounces off the wall and follows a new direction in another straight line following the laws of symmetric reflection. The robot needs to escape through an opening on the wall that has a minimum length of one unit. The robot can only escape through the opening if it reaches any point of the opening with a non-zero angle.We present an efficient algorithm for which the robot is guaranteed to find the opening if there is any or declare that there is none. We prove that the algorithm works if and only if the sides of the rectangle are co-prime. As a by-product of our main result, we also provide some interesting results related to the coverage of the interior of the rectangle when the robot follows similar algorithms to escape from the rectangular room.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.025
GPT teacher head0.255
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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