# LTLf Adaptive Synthesis for Multi-Tier Goals in Nondeterministic Domains

arXiv: https://arxiv.org/abs/2504.20983 · HTML: https://mlsanity.com/paper/2504.20983/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 29 references that are in the map.
- First posted on arXiv 29 Apr 2025.

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

- [Soft Goals Can Be Compiled Away](https://mlsanity.com/paper/1401.3491/) (2014)
- [LTLf Synthesis with Fairness and Stability Assumptions](https://mlsanity.com/paper/1912.07804/) (2019)
- [Multi-tier Automated Planning for Adaptive Behavior (Extended Version)](https://mlsanity.com/paper/2002.12445/) (2020)

## Built on by (most cited first, 1 of 1)

- [Optimal LTLf Synthesis](https://mlsanity.com/paper/2605.11544/) (2026)

## Abstract (arXiv)

We study a variant of LTLf synthesis that synthesizes adaptive strategies for achieving a multi-tier goal, consisting of multiple increasingly challenging LTLf objectives in nondeterministic planning domains. Adaptive strategies are strategies that at any point of their execution (i) enforce the satisfaction of as many objectives as possible in the multi-tier goal, and (ii) exploit possible cooperation from the environment to satisfy as many as possible of the remaining ones. This happens dynamically: if the environment cooperates (ii) and an objective becomes enforceable (i), then our strategies will enforce it. We provide a game-theoretic technique to compute adaptive strategies that is sound and complete. Notably, our technique is polynomial, in fact quadratic, in the number of objectives. In other words, it handles multi-tier goals with only a minor overhead compared to standard LTLf synthesis.