Approximate-directed

Referring to a method, process, or result that is guided by an estimation or educated guess, aiming for a specific outcome without requiring absolute precision or certainty. It suggests a general direction or course of action rather than a strictly defined, deterministic path. This approach allows for flexibility, adaptability, and often, the exploration of solutions when precise information is unavailable or difficult to obtain, while maintaining a clear goal or purpose. The emphasis is on arriving at a satisfactory outcome, acknowledging the potential for minor deviations or adjustments along the way.

Approximate-directed meaning with examples

• The search algorithm used an approximate-directed strategy to locate the target files. It relied on keyword matching and fuzzy logic, allowing for a quicker, but potentially less precise, retrieval compared to a full-text search. The approach saved considerable processing time, and the trade-off was acceptable given the large data volume.
• The project team employed an approximate-directed budgeting technique, using initial estimations and percentage allocations. This allowed for an expedited start and helped in securing immediate resources. Detailed cost analysis was delayed to gain more information. It allowed for flexibility in the resource allocation as the project progressed.
• During the emergency response, an approximate-directed evacuation plan was initiated. Due to rapidly changing conditions, precise information about the location of all individuals was unavailable. The plan relied on general guidelines and radio communication, enabling a rapid and effective response to the immediate situation despite its inherent uncertainties.
• The AI used an approximate-directed learning algorithm to navigate through the virtual environment. It was trained on a limited dataset, and thus was only equipped with partial information and lacked precision in its predictions. Its actions were driven by general rules and probabilistic reasoning, allowing for exploration and adaptive behaviour.