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Record W2135923283

Restricted Universes of Partizan Misere Games

2013· article· en· W2135923283 on OpenAlexvenueno aff
Rebecca Milley

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typearticle
Languageen
FieldComputer Science
TopicArtificial Intelligence in Games
Canadian institutionsnot available
Fundersnot available
KeywordsModuloUniverseQuotientMathematicsGeneralizationNatural (archaeology)Computer scienceCombinatoricsPhysics
DOInot available

Abstract

fetched live from OpenAlex

This thesis considers three restricted universes of partizan combinatorial games and finds new results for misere play using the recently-introduced theory of indistinguishability quotients.\nThe universes are defined by imposing three different conditions on game play: alternating, dicot (all-small), and dead-ending. General results are proved for each main universe, which in turn facilitate detailed analysis of specific subuniverses. In this way, misere monoids are constructed for alternating ends, for pairs of day-2 dicots, and for normal-play numbers, as well as for sets of positions that occur in variations of nim, hackenbush, and kayles, which fall into the alternating, dicot, and dead-ending universes, respectively.\nSpecial attention is given to equivalency to zero in misere play. With a new sufficiency condition for the invertibility of games in a restricted universe, the thesis succeeds in demonstrating the invertibility (modulo specific universes) of all alternating ends, all but previous-win alternating non-ends, all but one day-2 dicot, over one thousand day-3 dicots, hackenbush ‘sprigs’, dead ends, normal-play numbers, and partizan kayles positions.\nConnections are drawn between the three universes, including the recurrence of monoids isomorphic to the group of integers under addition, and the similarities of universe-specific outcome determinants. Among the suggestions for future research is the further investigation of a natural and promising subset of dead-ending games called placement games.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.152
Teacher spread0.147 · 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.

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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicArtificial Intelligence in GamesFrench-language works237,207