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Record W2917471116

Extending ConGolog to allow partial ordering

2000· article· en· W2917471116 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)Computer sciencePrologProgramming languageSet (abstract data type)InterpreterImplementationPartial evaluationLanguage constructDeterminismTheoretical computer science
DOInot available

Abstract

fetched live from OpenAlex

. In this paper we extend the high level execution language ConGolog (developed at the University of Toronto) by adding to it a new construct which we call the htn-construct. The new construct improves ConGolog by allowing easy specification of non-determinism when a partial ordering between a set of actions needs to be maintained. Furthermore, it allows temporal constraints to be specified easily. We present an implementation of the htn-construct in PROLOG which can be directly added to PROLOG implementations of ConGolog interpreters. 1 Introduction Golog [8] and ConGolog [3--5] are two main high level execution languages developed recently (in the 90's) by the Cognitive Robotics group at the University of Toronto. The approach to write programs in these languages for high level control of robots and other agents in a dynamic and incompletely specified world is proposed as an alternative to the traditional approach based on plan synthesis. The approach of writing programs in Golog/C...

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.807
Threshold uncertainty score0.627

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)0.0010.000

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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