Tabu search for SAT (TSAT)
Algorithms AIMech:TabuSearchForSAT DRAFT
The SAT-specific basic tabu-search method described by Mazure, Saïs and Grégoire in 1997, which systematically excludes recently flipped variables using a fixed-length chronological FIFO list, updates that list after each flip and permits no aspiration override in the surrounding GSAT assignment-search setting.
Identity Notes & Concept Scope
The1997 Mazure et al. SAT procedure uses systematic fixed FIFO variable exclusion with no aspiration; broader TabuSearch is a framework rather than this source-scoped algorithm. Timid TSAT in the earlier GenSAT family is separate and remains pending underowner298. Later UBCSAT1.0.0 GSAT/TABU is explicitly versioned contextual evidence; unreported paper tie/reset/all-tabu behavior is not filled from code. At clean merged base14e9168ee3496e914545ae5c449e3ee190f0294b, the current inventory has786 native and442 pinned AIO records:4876 identity-field occurrences,3723 normalized values, and no candidate collision. Four full-checkout searches included ignored and hidden files; all1329 distinct matching contents (23381 occurrences) were read by the attributed root/team partitions, with18 contextual fields across ten neighboring records assessed separately. This is bounded identity evidence, not proof of universal semantic absence.
Claims & Grounded Evidence
5 Claims
Scope
#gsat-model-finding-context
TSAT is introduced in the GSAT model-finding setting for CNF formulas, using complete Boolean assignments and single-variable flips. The surrounding GSAT presentation uses random initial assignments, per-attempt flip budgets and an outer attempt budget; its best-score flip can have zero or negative gain. Figure 3 is explicitly basic GSAT and is not a complete dedicated TSAT pseudocode.
Mechanism
#systematic-fifo-variable-exclusion
TSAT maintains a fixed-length, chronologically ordered FIFO list of flipped variables. A variable in the tabu list is forbidden from being flipped again while it remains listed. The list is updated every time a flip is made, so the restriction systematically tracks recent variable changes rather than being applied only after a detected local minimum.
Mechanism
#no-aspiration-and-attribute-memory
The described basic TSAT uses no aspiration criterion: a favorable clause score does not by itself override tabu status. Its list stores variables rather than complete forbidden truth assignments. Thus the memory restricts move attributes and does not constitute a set of all previously visited search states.
Mechanism
#random-walk-branch-distinction
TSAT removes the additional random-walk branch used by RWS-GSAT and instead applies the systematic tabu restriction. This does not mean that every choice becomes deterministic. The paper retains the random-start GSAT setting and discusses random basic-GSAT ties, without restating a complete TSAT tie or reset specification.
Scope
#versioned-gsat-tabu-selector
In the separately versioned UBCSAT 1.0.0 archive, the unweighted GSAT/TABU registration cites Mazure, Saïs and Grégoire’s CP95 work. Its PickGSatTabu selector filters variables using the last-change cutoff, scans the non-tabu variables for a minimum cached score, and selects uniformly when several candidates tie for that minimum. These are static implementation details of that archive, not certification that it reproduces every convention of the 1997 experimental program.
⚠️ Curated Limitations & Negative Results
- The 1997 presentation does not supply a complete dedicated TSAT pseudocode. Initialization and reset of tabu memory, ties, the discrete tenure boundary and empty-admissible-set behavior need explicit operational conventions. Figure 3 is basic GSAT; later implementation choices must not be silently substituted for the original account.
- A declared integer tenure and variable universe are needed. For n>0 variables and a tabu set of at most T distinct variables, 0≤T<n ensures that some variable is admissible. If T≥n, all variables can become tabu without an intervening reset. The inspected paper gives no general all-tabu fallback or aspiration escape; a fitted fractional tenure also needs an integer convention.
- Finite unsuccessful search is not an UNSAT certificate, and recent-variable exclusion does not prove global cycle freedom or eventual success. On the unsatisfiable conjunction of all four two-variable clauses, every flip has zero gain; tenure one can permit alternating x,y flips that revisit an assignment after four steps and an augmented assignment/list state after the fifth, absent an intervening cutoff or reset. This is a hand boundary example, not an observed run.
- The best admissible flip need not improve the clause score, and a useful move can be tabu. No-aspiration TSAT differs from tabu configurations with aspiration, adaptive tenure or longer-term intensification and diversification. Constant-time circular FIFO access does not establish constant-time evaluation of all flips or constant-time search.
- The displayed linear formula for an experimentally best tabu-list length is a fit for the reported random K-SAT studies, not a universal optimum, theorem, rounding rule or guarantee for structured SAT. The paper identifies dynamic lengths and structured examples as further work; no fixed tenure is mandated here for every problem.
- Table 1 reports time and flip averages on solved instances, with solved percentages relative to an approximately 50% expected satisfiable subset at the phase transition. These denominators and the common C/Linux/Pentium platform, budgets and tested distributions limit interpretation. The comparisons do not establish universal speedups, exact satisfiable-instance success rates or whole-solver complexity, and no benchmark was reproduced.
- The CP95 reference, the 1997 paper and later GSAT/TABU documentation remain distinct versions. The inspected UBCSAT selector has no explicit zero-candidate branch before reading candidate index zero; complete infrastructure and runtime behavior were not audited, so no observed implementation failure is asserted. The earlier timid TSAT and the clause-focused WalkSAT/TABU/null-move variants are not aliases of this scoped method.
Artificial Intelligence Ontology (AIO) Grounding
Explicit AIO Snapshot Assessment: No Match
Rationale: Symbolic SAT-specific search, with a fixed supplied objective and recency restrictions, is not a model or necessarily an ML training task. No mapping is forced from generic memory, score or stochastic vocabulary.
Search Scope: At clean merged base14e9168ee3496e914545ae5c449e3ee190f0294b, the current inventory has786 native and442 pinned AIO records:4876 identity-field occurrences,3723 normalized values, and no candidate collision. Four full-checkout searches included ignored and hidden files; all1329 distinct matching contents (23381 occurrences) were read by the attributed root/team partitions, with18 contextual fields across ten neighboring records assessed separately. This is bounded identity evidence, not proof of universal semantic absence. Exact pinned AIO CLASS neighborhoods and incident edges remain the separately accepted research assessment; 9 examined targets retain their individual rejection rationales. Shared score, memory or randomness vocabulary does not make symbolic SAT search a neural architecture or an ML training procedure.
| Examined AIO Candidate | Rejection Reason |
|---|---|
AIO:ReasoningLLM
|
The target is a language model, not a Boolean assignment search. |
AIO:TrainingStrategy
|
A SAT-specific move restriction need not preprocess or train an ML model. |
AIO:MachineLearningTask
|
Bookkeeping recent flips does not require a process that learns from data. |
AIO:ReinforcementLearning
|
Clause scores and exploration do not establish a learned policy or value function. |
AIO:MarkovChain
|
An augmented-state stochastic representation does not by itself map this named SAT search to the pinned network/model class and its hidden-layer relation. |
AIO:ArtificialNeuralNetwork
|
No connected artificial-neuron network is required. |
AIO:MemoryAugmentedLLM
|
A FIFO variable list is not external memory in a language model. |
AIO:MemoryCellLayer
|
A list of forbidden variables is not the pinned neural cell layer. |
AIO:HopfieldNetwork
|
Boolean flips with tabu restrictions do not require a symmetric recurrent neural memory. |
Evidence Sources & Primary Literature
2 Sources| Source ID | Publication / Document | Type / Access | Reference & Checksum |
|---|---|---|---|
mazure1997
|
Bertrand Mazure, Lakhdar Saïs, Éric Grégoire
|
primary paper
full_text
|
sha256:d5593e3e1a1e…
|
ubcsat1-gsat-tabu
|
Dave Tompkins, UBCSAT project
|
official documentation
documentation
|
sha256:62a15f14ea22…
|
Curation Provenance
Curator: Codex
Method: ai_assisted
Model: GPT-6
Created: 2026-10-15T23:35:54Z
Updated: 2026-10-15T23:35:54Z
Source File:
data/curated/TabuSearchForSAT.yaml