Decomposing causality into its synergistic, unique, and redundant components

DOI: 10.1098/rsta.2021.0150

Central Idea: This paper introduces SURD (Synergistic-Unique-Redundant Decomposition), a novel framework for quantifying causality by decomposing it into its synergistic, unique, and redundant components based on information theory. SURD overcomes limitations of existing causal inference methods, especially in complex systems with nonlinear dependencies, stochasticity, and hidden variables.

Key Concepts:

• Causality vs. Correlation/Association: The paper emphasizes the distinction between causality (physical influence), correlation (monotonic association), and association (statistical relationship). SURD focus ...