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TI$^2$PS: A Topology-Informed Inverse Design Framework for Stochastic Multicellular Pattern Formation

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

This study proposes a novel framework to estimate parameters for reproducing target multicellular patterns using an agent-based model (ABM). Two major challenges in multicellular ABMs are estimating cell-level parameters (agent-specific variables) and quantitatively evaluating the topological characteristics of multicellular arrangements under stochastic cell proliferation and death. To address these challenges, we integrate two approaches: Betti vectors and inverse surrogate modeling. The Betti vectors obtained through topological data analysis can consistently represent features of a wide ra

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