2025/03/20 by Yin-Jie Ma, Zhi‐Qiang Jiang, Ma, Yin-Jie +7 · 1 citation
Computer Science · Social Sciences · #Artificial Intelligence in Games #Evolutionary Game Theory and Cooperation #FOS: Physical sciences #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.2503.15923
openalex publication_date 2025/03/20 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28
In distributed systems, knowledge of the network structure of the connections among the unitary components is often a requirement for an accurate prediction of the emerging collective dynamics. However, in many real-world situations, one has, at best, access to partial connectivity data, and therefore the entire graph structure needs to be reconstructed from a limited number of observations of the dynamical processes that take place on it. While existing studies predominantly focused on reconstructing traditional pairwise networks, higher-order interactions remain largely unexplored. Here, we introduce three methods to reconstruct a simplicial complex structure of connection from observations of evolutionary games that take place on it, and demonstrate their high accuracy and excellent overall performance in synthetic and empirical complexes. The methods have different requirements and different complexity, thereby constituting a series of approaches from which one can pick the most appropriate one given the specific circumstances of the application under study.