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Record W2247630165 · doi:10.1017/cbo9780511807251.008

Tigers and Goats is a draw

2009· book-chapter· en· W2247630165 on OpenAlexaff
Lim Yew Jin, Jürg Nievergelt

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldComputer Science
TopicArtificial Intelligence in Games
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

. Bagha Chal, or “Moving Tiger”, is an ancient Nepali board game also known as Tigers and Goats. We briefly describe the game, some of its characteristics, and the results obtained from an earlier computer analysis. As in some other games such as Merrill's, play starts with a placement phase where 20 pieces are dropped on the board, followed by a sliding phase during which pieces move and may be captured. The endgame sliding phase had been analyzed exhaustively using retrograde analysis, yielding a database consisting of 88,260,972 positions, which are inequivalent under symmetry. The placement phase involves a search of 39 plies whose game tree complexity is estimated to be of the order 1041. This search has now been completed with the help of various optimization techniques. The two main ones are: confronting a heuristic player with an optimal opponent, thus cutting the search depth in half; and constructing a database of positions halfway down the search tree whose game-theoretic value is determined exhaustively. The result of this search is that Tigers and Goats is a draw if played optimally.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.525
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.266
Teacher spread0.232 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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