Abstraction of Situation Calculus Concurrent Game Structures
Bibliographic record
Abstract
We present a general framework for abstracting agent behavior in multi-agent synchronous games in the situation calculus, which provides a first-order representation of the state and allows us to model how plays depend on the data and objects involved. We represent such games as action theories of a special form called situation calculus synchronous game structures (SCSGSs), in which we have a single action "tick" whose effects depend on the combination of moves selected by the players. In our framework, one specifies both an abstract SCSGS and a concrete SCSGS, as well as a refinement mapping that specifies how each abstract move is implemented by a Golog program defined over the concrete SCSGS. We define notions of sound and complete abstraction with respect to a mapping over such SCSGS. To express strategic properties on the abstract and concrete games we adopt a first-order variant of alternating-time mu-calculus mu-ATL-FO. We show that we can exploit abstraction in verifying mu-ATL-FO properties of SCSGSs under the assumption that agents can always execute abstract moves to completion even if not fully controlling their outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".