AIAug 24, 2015

A note on the complexity of the causal ordering problem

arXiv:1508.05804v26 citations
AI Analysis

This is an incremental result that clarifies a long-standing intractability issue for researchers in causal reasoning and systems analysis.

The paper tackles the computational complexity of Simon's causal ordering problem, proving that the classical algorithm is NP-Hard and analyzing the best available solution's time complexity as O(|V|·|S|).

In this note we provide a concise report on the complexity of the causal ordering problem, originally introduced by Simon to reason about causal dependencies implicit in systems of mathematical equations. We show that Simon's classical algorithm to infer causal ordering is NP-Hard---an intractability previously guessed but never proven. We present then a detailed account based on Nayak's suggested algorithmic solution (the best available), which is dominated by computing transitive closure---bounded in time by $O(|\mathcal V|\cdot |\mathcal S|)$, where $\mathcal S(\mathcal E, \mathcal V)$ is the input system structure composed of a set $\mathcal E$ of equations over a set $\mathcal V$ of variables with number of variable appearances (density) $|\mathcal S|$. We also comment on the potential of causal ordering for emerging applications in large-scale hypothesis management and analytics.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes