NeFut Logo NeFut
Admin Login

[CS.AI] Expansion Counts under Standard A* Tie-Breaking Strategies

Published at: 2026-09-23 22:00 Last updated: 2026-09-24 00:40
#algorithm #AI #optimization

In A* search, when several nodes share the same $f$ value, a tie‑breaking rule determines which state is expanded next. This paper examines nine standard tie‑breaking strategies and, assuming a consistent heuristic, constructs positive‑cost instances that yield an arbitrarily large additive expansion gap between any pair of strategies. A parameterized unit‑cost grid example shows that the expansion‑count ratio between low‑$h$ with FIFO and LIFO can be unbounded. We also study unit‑cost search where non‑goal nodes have $h=0$: exact heuristic values near the goal produce complementary extremal outcomes—low $h$ minimizes the remaining expansions within the perfect region, while high $h$ maximizes the total expansions when every final‑plateau state with $h=1$ is a goal predecessor. Finally, using the weighted evaluation function $f_{\alpha}=g+\alpha h$ and the same $h=0$ condition, any weight $0\le\alpha$ leads to analogous extreme expansion behavior.

Review

Original Source: https://arxiv.org/abs/2609.23293

[h] Back to Home