Greedy best-first search
Algorithms AIMech:GreedyBestFirstSearch DRAFT
Aliases: GBFS
A best-first search algorithm that prioritizes open nodes by a heuristic estimate of remaining cost to a goal, without adding the cost already incurred to that priority.
Identity Notes & Concept Scope
The identity is heuristic-only global best-first selection, not every algorithm described as greedy. Hill climbing and beam search restrict the available candidates differently. The accumulated cost may still be stored for reconstructing or measuring a solution; it is omitted from the primary priority key. No normalized identity match was found across the 442 AIO and 124 prior native records; ignored-inclusive text hits in the main checkout were prior discovery leads, source citations and search-order contrasts, plus incidental dependency substrings, not existing concept records.
Claims & Grounded Evidence
2 Claims
Mechanism
#search-procedure
Select a node with minimum heuristic value h from the open frontier, expand it, and place eligible successors on that frontier until a selected goal or another stopping condition is reached. The cost-to-date g does not contribute to this heuristic-only primary ranking.
Limitation
#speed-qualification
Heuristic-only ordering is the greedy endpoint discussed in weighted-search studies. The cited study cautions that moving toward this endpoint need not reduce search effort; its empirical explanations are not universal runtime guarantees.
⚠️ Curated Limitations & Negative Results
- The priority rule supplies no user-chosen fixed bound on solution suboptimality. Any post-hoc bound requires additional lower-bound information and assumptions.
- Tie-breaking and duplicate handling remain consequential implementation choices. Completeness is not asserted for arbitrary infinite spaces or memory-pruned variants.
- A strong cost-to-go heuristic does not by itself establish universally fast search; no empirical correlation threshold is treated as a general theorem.
Artificial Intelligence Ontology (AIO) Grounding
Explicit AIO Snapshot Assessment: No Match
Rationale: No suitable AIO counterpart for this graph/state-space search procedure was identified in the inspected snapshot. Using graphs, evaluation functions or a search subroutine in an AI system does not equate the algorithm with a learned model, a learning task or a mathematical function.
Search Scope: All 442 pinned AIO labels and scoped synonyms and 124 preceding native identities were compared. Both updated checkouts were searched including hidden and ignored files. Exact CLASS nodes and edges for GraphLanguageModel, ReasoningLLM, NeuroSymbolicLLM, MachineLearningTask, MathematicalFunction and ReinforcementLearning were inspected, alongside semantic search for search, planning, heuristic, path, traversal, symbolic, reasoning and graph terminology.
| Examined AIO Candidate | Rejection Reason |
|---|---|
AIO:GraphLanguageModel
|
A language model operating on structured graph representations is not a graph traversal or shortest-path algorithm. |
AIO:ReasoningLLM
|
Language-task deductive inference does not denote general state-space search. |
AIO:NeuroSymbolicLLM
|
A language-model architecture combining neural and symbolic components is not the search procedure itself. |
AIO:MachineLearningTask
|
Building methods that learn from data is not the identity of an algorithm traversing a specified graph. |
AIO:MathematicalFunction
|
The search procedure is distinct from the mathematical functions it may evaluate. |
AIO:ReinforcementLearning
|
A learning task balancing exploration and exploitation is distinct from deterministic graph/state-space traversal. |
Evidence Sources & Primary Literature
2 Sources| Source ID | Publication / Document | Type / Access | Reference & Checksum |
|---|---|---|---|
method-source
|
Christopher Wilt, Jordan Thayer, Wheeler Ruml
|
primary paper
full_text
|
ID: doi:10.1609/socs.v1i1.18182
sha256:cfc3cf8f422b…
|
weighted-search-study
|
Christopher Wilt, Wheeler Ruml
|
primary paper
full_text
|
ID: doi:10.1609/socs.v3i1.18250
sha256:f1cd583c7e8f…
|
Curation Provenance
Curator: Codex
Method: ai_assisted
Model: GPT-6
Created: 2026-10-11T05:44:44Z
Updated: 2026-10-11T05:44:44Z
Source File:
data/curated/GreedyBestFirstSearch.yaml