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Record W1997980548 · doi:10.5539/mas.v4n5p196

Study for solving the path on the three-dimensional surface based on Cellular Automata method

2010· article· en· W1997980548 on OpenAlexvenueno aff

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsCellular automatonShortest path problemAsynchronous cellular automatonPath (computing)Computer scienceDimension (graph theory)Surface (topology)Interval (graph theory)Mobile automatonDiscretizationSimple (philosophy)Ant colony optimization algorithmsAlgorithmMathematicsMathematical optimizationAutomatonTheoretical computer scienceCombinatoricsAutomata theory

Abstract

fetched live from OpenAlex

For the path optimization problem on the irregular surface of three-dimension, three-dimensional surface is discretized with grid. Based on the parallel character of cellular automata in the cellular space, with the dynamic cellular neighbors , the time evolution interval is defined as the minimum remaining weight. The new shortest path algorithm is structured, based on cellular automaton model. That is to say, through the simple rules of evolution of cellular state, the shortest path is got. The method can achieve the efficiency of ant colony algorithm, and a new way of application of the Cellular Automata model is provided.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.285
Teacher spread0.251 · 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 designSimulation or modeling
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
Published2010
Admission routes1
Has abstractyes

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