Accessibility Relation and Nonmonotonic Reasoning (Extended Abstract)
Bibliographic record
Abstract
) Li-Yan Yuan, Jia-Huai You Department of Computing Science University of Alberta Edmonton, Canada T6G 2H1 fyuan, youg@cs.ualberta.ca Hajime Sawamura Institute for Social Information Science Fujitsu Laboratories Numazu, Shizuoka, 410-03 Japan hajime@iias.flab.fujitsu.co.jp Abstract. By studying the accessibility relations in logics of knowledge and belief, we reveal that almost all prominent nonmonotonic reasoning semantics can be characterized in terms of standard Kripke structures by altering the accessibility relation. This result not just extends the expressive power of the Kripke structure but also clearly demonstrates that the nonmonotonic reasoning is a reasoning about implicit belief and therefore can be characterized by various logics of belief. 1 Introduction The epistemic notions of knowledge and belief have most commonly been modeled by means of possible world semantics, often in terms of Kripke Structure [5, 6]. In a Kripke structure , the fundamental notions are tho...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".