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Record W2112727145 · doi:10.1109/.2005.1467202

Optimality Zone Algorithms for Hybrid Systems Computation and Control: From Exponential to Linear Complexity

2005· article· en· W2112727145 on OpenAlex

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

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsMcGill University
FundersUniversity of Illinois at Urbana-Champaign
KeywordsComputationOptimal controlAlgorithmState (computer science)Sequence (biology)ScheduleHybrid systemMathematical optimizationComputer scienceComputational complexity theorySet (abstract data type)MathematicsTime complexityExponential function

Abstract

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Necessary conditions were obtained by Shaikh and Caines (2002, 2003 and 2004) for hybrid optimal control problems (HOCPs) which resulted in a general hybrid maximum principle (HMP); further, a class of efficient, provably convergent hybrid maximum principle (HMP) algorithms were obtained based upon the HMP. The notion of optimality zones (OZs) (2004) was introduced as a theoretical framework enabling the computation of optimal schedules for HOCPs (i.e., discrete state sequences with the associated switching times and states). This paper presents the algorithm HMPZ which fully integrates the prior computation of the OZs into the HMP algorithms. Adding (i) the computational investment in the construction of the OZs for a given HOCP, and (ii) the complexity of the computation of the optimal schedule, optimal switching time and state sequence, and the optimal continuous control input, yields a complexity estimate for the algorithm (HMPZ) which is linear (i.e., O(L)) in the number of switching times L; this is to be compared with the geometric (i.e. O(|Q| <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</sup> )) growth of a direct combinatoric search over the set of schedules, where Q denotes the discrete state set of the hybrid system

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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)0.000
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.260
Teacher spread0.236 · 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

Citations36
Published2005
Admission routes1
Has abstractyes

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