Planning with Minimal Disruption

TL;DR

This paper introduces the concept of plan disruption in planning, proposing methods to generate plans that balance minimal state modification with goal achievement, validated through experiments.

Contribution

It formally defines plan disruption and develops planning methods that optimize both action costs and minimal state changes.

Findings

Effective planning methods balance action costs and minimal disruption.

Experimental results demonstrate practical feasibility across benchmarks.

Reformulated tasks successfully generate balanced plans.

Abstract

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.