接入 API · 个人 AI 解读连接自己的模型解读资讯,浏览新闻无需配置。
返回资讯列表
前沿研究社区 / 第三方国际

Expansion Counts under Standard A* Tie-Breaking Strategies on the Final Plateau

arXiv 人工智能论文 · 发布
今日摘要使用自己的 API,仅供个人查看

来源摘要

arXiv:2609.23293v1 Announce Type: new Abstract: In the A* search algorithm, the tie-breaking strategies for nodes with the same $f$-value determines which states A* expands on the final $f$-layer. For nine standard tie-breaking strategies, we show that under a consistent heuristic, every pair has positive-cost instances favoring each strategy over the other by an arbitrarily large additive expansion gap. A parameterized unit-cost grid example also gives unbounded expansion-count ratios between low-$h$ with FIFO and LIFO. In unit-cost search with $h > 0$ at non-goals, exact heuristic values near the goal lead to complementary extremal results: low-$h$ minimizes the number of remaining expansions from a common configuration within the perfect region, while high-$h$ maximizes the total number of expansions when every final-plateau state with $h=1$ is a goal predecessor. Finally, with the evaluation function $f_{\alpha} = g + \alpha h$, when $h>0$ at non-goals, every heuristic weight $0 \leq \alpha<1$ eliminates tie-breaking sensitivity, and all tie-breaking strategies expand the same set of states.

阅读原始来源
来源
arXiv 人工智能论文 · 社区 / 第三方
来源发布
2026/09/22 12:00
首次采集
2026/09/23 11:59

本文为公开信息索引与摘要,详情及后续变化请以原始来源为准。

把 AI 雷达放到桌面

在支持安装的浏览器中,可以将本站作为应用打开。

安装入口取决于浏览器;应用和网站使用同一份最新内容。

查看完整安装指南