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Record W3177340988 · doi:10.1109/lcsys.2021.3092950

An Isochron-Based Solution to the Target Defense Game Against a Faster Invader

2021· article· en· W3177340988 on OpenAlexafffund
Han Fu, Hugh H. T. Liu

Bibliographic record

VenueIEEE Control Systems Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicGuidance and Control Systems
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsochron datingSaddle pointDifferential gameComputer scienceGame theoryMathematical economicsRange (aeronautics)SaddleRepeated gameStrategyMathematical optimizationArtificial intelligenceMathematicsIsochronEngineering

Abstract

fetched live from OpenAlex

This letter studies a target defense game between two defenders and a faster moving invader. We propose a novel approach that solves the saddle point strategy from a family of time-to-capture isochrons. We show that the game can be viewed as a pursuit-evasion game between the invader and the isochrons, where the latter are controlled by the defenders. The optimal defending strategy is the one that forces the invader to isochrons with shorter time-to-capture most efficiently. The proposed method is validated in a special case with zero capture range, where we prove that the saddle point strategy is optimal regardless of other players' behaviors. In addition, the isochrons are shown to be semipermeable, and the barrier of the target defense game is solved.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.193
Teacher spread0.185 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations12
Published2021
Admission routes2
Has abstractyes

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