Cognition · Software component

Bounded-Suboptimal Search Planner

Software componentCognitionCognition & Memoryarc:BoundedSuboptimalSearchPlanner

A graph search planner that inflates the heuristic weight (g(n)+w*h(n), w>1) to expand fewer nodes, returning paths at most w times optimal cost.

Responsibility. Returns a near-optimal path within a bounded cost factor under tight planning deadlines.

Also known as: Weighted A* planner

Variant of Graph Search Planner abstract

When to choose. Choose for real-time games, robots under time pressure and interactive systems where responsiveness outweighs optimality and cost may exceed optimal by up to factor w.

Direct neighbourhood (hover for relationship types)

Relationships

alternative to variability

Optimal Heuristic Search Planner Ch5.6

Design guidance

SHOULD be used when near-optimal solutions suffice and decisions must arrive within a strict time budget.
MUST NOT be used where provably shortest paths are mandatory.

Quantitative guidance

As stated by the sources; verify before use.

w = 2.0 expanded 95 instead of 380 nodes, 47 ms vs 185 ms, yielding a 49 m path vs 47 m optimal (~4% longer) (Ch5.6).
Solution cost is guaranteed at most w times optimal (Ch5.6).

Classification

Patterns: Weighted A*Bounded suboptimality
Quality attributes: Performance efficiency (ISO/IEC 25010)
Risks mitigated: Plans arriving after the control deadline

Sources

Ch5.6: T. Nguyen, "A* Search and Replaning," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.6. ISBN: 9798244538229.