Cognition · Software component

Memory-Bounded Search Planner

Software componentCognitionCognition & Memoryarc:MemoryBoundedSearchPlanner

A graph search planner that performs depth-first search under an iteratively increasing f-value threshold, storing only the current path instead of open and closed lists.

Responsibility. Finds a path within O(b*d) memory by trading repeated node re-expansion for storage.

Also known as: IDA* planner, Iterative Deepening A*

Variant of Graph Search Planner abstract

When to choose. Choose when memory is scarcer than time: embedded systems, mobile devices with strict memory budgets, or search spaces far exceeding available RAM.

Direct neighbourhood (hover for relationship types)

Relationships

deployed on structural

Edge Device abstract Ch5.6

alternative to variability

Optimal Heuristic Search Planner Ch5.6

Design guidance

SHOULD be used on memory-constrained embedded or mobile hosts; servers with abundant memory SHOULD prefer standard A* for speed.

Quantitative guidance

As stated by the sources; verify before use.

GPS example: 500,000 explored nodes x 24 bytes = 12 MB closed list for A*; IDA* needs ~4.8 KB for a 200-edge path (Ch5.6).
IDA* can increase total node expansions by 3-5x due to re-expansion across iterations (Ch5.6).

Classification

Patterns: Iterative Deepening A*Time-memory trade-off
Quality attributes: Performance efficiency (ISO/IEC 25010)
Risks mitigated: Memory exhaustion on very large graphs

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.