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arXiv · 2502.12707

CausalMan: A physics-based simulator for large-scale causality

Nicholas Tagliapietra·Juergen Luettin·Lavdim Halilaj·Moritz Willig·Tim Pychynski·Kristian Kersting
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Abstract

A comprehensive understanding of causality is critical for navigating and operating within today's complex real-world systems. The absence of realistic causal models with known data generating processes complicates fair benchmarking. In this paper, we present the CausalMan simulator, modeled after a real-world production line. The simulator features a diverse range of linear and non-linear mechanisms and challenging-to-predict behaviors, such as discrete mode changes. We demonstrate the inadequacy of many state-of-the-art approaches and analyze the significant differences in their performance and tractability, both in terms of runtime and memory complexity. As a contribution, we will release the CausalMan large-scale simulator. We present two derived datasets, and perform an extensive evaluation of both.

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Nicholas Tagliapietra, Juergen Luettin, Lavdim Halilaj, Moritz Willig, Tim Pychynski, Kristian Kersting. 2025-02-18. CausalMan: A physics-based simulator for large-scale causality. https://arxiv.org/abs/2502.12707

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