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Record W2258235760 · doi:10.5555/2772879.2773380

Synchronous Games in the Situation Calculus

2015· article· en· W2258235760 on OpenAlexaff
Giuseppe De Giacomo, Yves Lespérance, Adrian R. Pearce

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2015
Typearticle
Languageen
FieldComputer Science
TopicLogic, Reasoning, and Knowledge
Canadian institutionsYork University
Fundersnot available
KeywordsSituation calculusAction (physics)Computer scienceCalculus (dental)Order (exchange)Process calculusFirst orderAlgebra over a fieldTheoretical computer scienceMathematicsArtificial intelligenceApplied mathematicsPure mathematics

Abstract

fetched live from OpenAlex

We develop a situation calculus-based account of multi-player synchronous games. These are represented as action theories called situation calculus synchronous game structures (SCSGSs) that involve a single action tick whose effects depend on the combination of moves chosen by the players. Properties of games, e.g., winning conditions, playability, weak and strong winnability, etc. can be expressed in a first-order variant of alternating-time mu-calculus. Computationally effective verification can be performed. SCSGSs can be viewed as a variant of the Game Description Language (CDL) where states are represented by first-order theories. Copyright © 2015, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.062
GPT teacher head0.308
Teacher spread0.246 · 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 designNot applicable
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

Citations1
Published2015
Admission routes1
Has abstractyes

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