Probabilistic Focal Search: Accelerating Bounded-Suboptimal Search via Lower-Bound Advancement
Bounded-suboptimal search seeks a solution within a factor $w$ of optimal while reducing search effort. Focal Search (FS) uses heuristic guidance within FOCAL, the frontier nodes eligible under the threshold $w f_{\min}$, but its deterministic policy may leave $f_{\min}$ unchanged for many expansions. We introduce Probabilistic Focal Search (PFS), which follows the FS guided choice with probability $p$ and expands a minimum-$f$ OPEN node with probability $1-p$. The latter branch encourages the lower bound to advance, enlarging FOCAL and admitting nodes that may lead to feasible solutions. By balancing guidance and lower-bound advancement, this mechanism can reduce time to a bounded soluti...
| Authors | Minh Vu Duc, Trung Le Huu, Hà Minh Hoàng et al. |
|---|---|
| Primary category | cs.AI |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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