# Planning with Dynamically Changing Domains

arXiv: https://arxiv.org/abs/2508.02697 · HTML: https://mlsanity.com/paper/2508.02697/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 49 references that are in the map.
- First posted on arXiv 26 Jul 2025.

## Builds on (most cited first, 6 of 6)

- [Qualitative Numeric Planning: Reductions and Complexity](https://mlsanity.com/paper/1912.04816/) (2019)
- [Compiling Uncertainty Away in Conformant Planning Problems with Bounded Width](https://mlsanity.com/paper/1401.3468/) (2014)
- [Bounded Situation Calculus Action Theories](https://mlsanity.com/paper/1509.02012/) (2015)
- [Generalized Planning as Heuristic Search: A new planning search-space that leverages pointers over objects](https://mlsanity.com/paper/2301.11087/) (2023)
- [Planning as Theorem Proving with Heuristics](https://mlsanity.com/paper/2303.13638/) (2023)
- [Learning to Ground Existentially Quantified Goals](https://mlsanity.com/paper/2409.20259/) (2024)

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

- [Petri Net Relaxation for Infeasibility Explanation and Sequential Task Planning](https://mlsanity.com/paper/2602.22094/) (2026)

## Abstract (arXiv)

In classical planning and conformant planning, it is assumed that there are finitely many named objects given in advance, and only they can participate in actions and in fluents. This is the Domain Closure Assumption (DCA). However, there are practical planning problems where the set of objects changes dynamically as actions are performed; e.g., new objects can be created, old objects can be destroyed. We formulate the planning problem in first-order logic, assume an initial theory is a finite consistent set of fluent literals, discuss when this guarantees that in every situation there are only finitely many possible actions, impose a finite integer bound on the length of the plan, and propose to organize search over sequences of actions that are grounded at planning time. We show the soundness and completeness of our approach. It can be used to solve the bounded planning problems without DCA that belong to the intersection of sequential generalized planning (without sensing actions) and conformant planning, restricted to the case without the disjunction over fluent literals. We discuss a proof-of-the-concept implementation of our planner.