Gridsolver
Computational state-space intelligence.
A computational framework for exploring large combinatorial spaces using multi-radix state encoding, relevance filtering and adaptive solver selection. Its aim is to work with complex possibilities without enumerating every combination.
Direct state indexing
A defined component within the proposed architecture, intended to support more reliable decisions and clearer system behaviour.
Entropy-based filtering
Structured processing and explicit criteria guide selection, interpretation or optimisation.
Solver selection and traceability
An area for progressive engineering, evaluation and refinement as the technology is developed.
The challenge.
Large discrete search spaces become difficult to inspect, filter and solve exhaustively.
How it works.
Multi-radix indices provide compact coordinates; semantic or entropy-based gating is proposed to filter candidates before adaptive solver selection.
Conceptual workflow, not a production system diagram.
Development position.
Research framework; state encoding is mathematically defined, while broad scale and efficiency claims require benchmarking.
Where it may apply.
Constrained optimisation, scheduling, configuration search and computational research.
Questions still open.
Memory costs, pruning correctness, solver-selection criteria and scaling under realistic workloads need measurement.