Abstraction, Reformulation, and Approximation: 5th International Symposium, SARA 2002, Kananaskis, Alberta, Canada, August 2-4, 2002, Proceedings
Bibliographic record
Abstract
Invited Presentations.- Model Checking and Abstraction.- Reformulation in Planning.- Spatiotemporal Abstraction of Stochastic Sequential Processes.- State Space Relaxation and Search Strategies in Dynamic Programming.- Invited Presentations.- Admissible Moves in Two-Player Games.- Dynamic Bundling: Less Effort for More Solutions.- Symbolic Heuristic Search Using Decision Diagrams.- On the Construction of Human-Automation Interfaces by Formal Abstraction.- Pareto Optimization of Temporal Decisions.- An Information-Theoretic Characterization of Abstraction in Diagnosis and Hypothesis Selection.- A Tractable Query Cache by Approximation.- An Algebraic Framework for Abstract Model Checking.- Action Timing Discretization with Iterative-Refinement.- Formalizing Approximate Objects and Theories: Some Initial Results.- Model Minimization in Hierarchical Reinforcement Learning.- Learning Options in Reinforcement Learning.- Approximation Techniques for Non-linear Problems with Continuum of Solutions.- Approximation of Relations by Propositional Formulas: Complexity and Semantics.- Abstracting Visual Percepts to Learn Concepts.- Short Presentations.- PAC Meditation on Boolean Formulas.- On the Reformulation of Vehicle Routing Problems and Scheduling Problems.- The Oracular Constraints Method.- Performance of Lookahead Control Policies in the Face of Abstractions and Approximations.- TTree: Tree-Based State Generalization with Temporally Abstract Actions.- Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction.- Research Summaries.- Abstracting Imperfect Information Game Trees.- Using Abstraction for Heuristic Search and Planning.- Approximation Techniques in Multiagent Learning.- Abstraction and Reformulation in GraphPlan.- Abstract Reasoning for Planning and Coordination.- Research Summary: Abstraction Techniques, and Their Value.- Reformulation of Non-binary Constraints.- Reformulating Combinatorial Optimization as Constraint Satisfaction.- Autonomous Discovery of Abstractions through Interaction with an Environment.- Interface Verification: Discrete Abstractions of Hybrid Systems.- Learning Semi-lattice Codebooks for Image Compression.- Research Summary.- Principled Exploitation of Heuristic Information.- Reformulation of Temporal Constraint Networks.
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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.058 | 0.014 |
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".