English

Diverse Planning with Simulators via Linear Temporal Logic

Artificial Intelligence 2025-10-21 v1 Multiagent Systems

Abstract

Autonomous agents rely on automated planning algorithms to achieve their objectives. Simulation-based planning offers a significant advantage over declarative models in modelling complex environments. However, relying solely on a planner that produces a single plan may not be practical, as the generated plans may not always satisfy the agent's preferences. To address this limitation, we introduce FBILTL\texttt{FBI}_\texttt{LTL}, a diverse planner explicitly designed for simulation-based planning problems. FBILTL\texttt{FBI}_\texttt{LTL} utilises Linear Temporal Logic (LTL) to define semantic diversity criteria, enabling agents to specify what constitutes meaningfully different plans. By integrating these LTL-based diversity models directly into the search process, FBILTL\texttt{FBI}_\texttt{LTL} ensures the generation of semantically diverse plans, addressing a critical limitation of existing diverse planning approaches that may produce syntactically different but semantically identical solutions. Extensive evaluations on various benchmarks consistently demonstrate that FBILTL\texttt{FBI}_\texttt{LTL} generates more diverse plans compared to a baseline approach. This work establishes the feasibility of semantically-guided diverse planning in simulation-based environments, paving the way for innovative approaches in realistic, non-symbolic domains where traditional model-based approaches fail.

Keywords

Cite

@article{arxiv.2510.17418,
  title  = {Diverse Planning with Simulators via Linear Temporal Logic},
  author = {Mustafa F. Abdelwahed and Alice Toniolo and Joan Espasa and Ian P. Gent},
  journal= {arXiv preprint arXiv:2510.17418},
  year   = {2025}
}
R2 v1 2026-07-01T06:47:19.461Z