# Planning with Minimal Disruption

arXiv: https://arxiv.org/abs/2508.15358 · HTML: https://mlsanity.com/paper/2508.15358/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 22 references that are in the map.
- First posted on arXiv 21 Aug 2025.

## Builds on (most cited first, 3 of 3)

- [Soft Goals Can Be Compiled Away](https://mlsanity.com/paper/1401.3491/) (2014)
- [On Learning Action Costs from Input Plans](https://mlsanity.com/paper/2408.10889/) (2024)
- [On Computing Plans with Uniform Action Costs](https://mlsanity.com/paper/2402.09877/) (2024)

## Abstract (arXiv)

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.