AWhat changed
Bellman applies dynamic-programming cost-to-go equations to positive-time finite routing and gives policy-initialized monotone successive approximations that reach the optimal travel cost after a bounded number of iterations.
Scientific scope
Bellman applies dynamic-programming cost-to-go equations to positive-time finite routing and gives policy-initialized monotone successive approximations that reach the optimal travel cost after a bounded number of iterations. The original model uses finitely many cities with strictly positive pairwise travel times and a fixed destination. Its initialization, recursion and iteration bound belong to that model. Nonnegative/negative weights, sparse-graph implementations and modern Bellman–Ford variants need their own conditions. The result does not provide a universal routing guarantee under arbitrary changing network conditions.
Evidence
Source-linked, scoped account of the original work. The published scope states the scientific assumptions and remaining verification limits. WRS has not independently certified the full proof, experimental result or system benchmark.
Contributors
- Richard Bellman · SCIENCE: Original source-listed scientific author of this scoped work; byline does not determine effort fractions.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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