寻找对初始状态改动最小的规划方案，实现目标与稳定性平衡。
Planning with Minimal Disruption
- 将规划扰动建模为优化目标，联合最小化动作成本与状态改动
- 在多个基准测试中成功生成兼顾成本与稳定性的均衡计划
- 适合需要保持原状、减少变动的智能系统部署场景
在许多规划应用中，我们关注的是找到对初始状态改动最小以达成目标的规划方案，这种概念称为计划扰动。本文首次形式化定义该概念，并提出多种基于规划的编译方法，旨在同时优化动作成本总和与计划扰动。实验结果表明，在不同基准测试中，重构后的任务可被有效求解，生成的计划在两个目标间实现良好平衡。
原文摘要 · Abstract (English)
In many planning applications, we might be interested in finding plans that minimally modify the initial state to achieve the goals. We refer to this concept as plan disruption. In this paper, we formally introduce it, and define various planning-based compilations that aim to jointly optimize both the sum of action costs and plan disruption. Experimental results in different benchmarks show that the reformulated task can be effectively solved in practice to generate plans that balance both objectives.
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