# Multi-tier Automated Planning for Adaptive Behavior (Extended Version)

arXiv: https://arxiv.org/abs/2002.12445 · HTML: https://mlsanity.com/paper/2002.12445/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2020.

## Built on by (most cited first, 4 of 4)

- [Flexible FOND Planning with Explicit Fairness Assumptions](https://mlsanity.com/paper/2103.08391/) (2021)
- [Abstraction of Nondeterministic Situation Calculus Action Theories -- Extended Version](https://mlsanity.com/paper/2305.14222/) (2023)
- [LTLf Best-Effort Synthesis in Nondeterministic Planning Domains](https://mlsanity.com/paper/2308.15188/) (2023)
- [LTLf Adaptive Synthesis for Multi-Tier Goals in Nondeterministic Domains](https://mlsanity.com/paper/2504.20983/) (2025)

## Abstract (arXiv)

A planning domain, as any model, is never complete and inevitably makes assumptions on the environment's dynamic. By allowing the specification of just one domain model, the knowledge engineer is only able to make one set of assumptions, and to specify a single objective-goal. Borrowing from work in Software Engineering, we propose a multi-tier framework for planning that allows the specification of different sets of assumptions, and of different corresponding objectives. The framework aims to support the synthesis of adaptive behavior so as to mitigate the intrinsic risk in any planning modeling task. After defining the multi-tier planning task and its solution concept, we show how to solve problem instances by a succinct compilation to a form of non-deterministic planning. In doing so, our technique justifies the applicability of planning with both fair and unfair actions, and the need for more efforts in developing planning systems supporting dual fairness assumptions.