The causal role of synergy in collective problem-solving
Submitted in 2025
The influence of network structure on a system’s capacity to solve complex problems is a central focus in collective intelligence research. However, the causal mechanisms through which structure shapes system-level outcomes remain poorly understood. Prior work has examined the relationship between network structure and performance at a coarse-grained level, paying limited attention to how solutions depend on information dynamics within groups. To explore these dynamics, we utilize an agent-based model, the Potions Task, which operationalizes problem-solving as a combinatorial process and is thereby ideal for studying collective problem-solving through information-theoretic analyses. We examine information-based metrics at the level of agent pairs across the network, analyzing their variation over time to determine how they predict problem-solving across network structures. Specifically, we measure redundancy (or conversely, synergy) of solutions discovered by agents with respect to the network’s global knowledge at a given time. While we replicate a well-established finding that small-world networks support efficient problem-solving, our results reveal a deeper mechanism where small-world networks achieve efficiency by balancing local redundancy with long-range synergy. Furthermore, we find synergy to be a consistent predictor of group performance, including in networks typically considered inefficient. Synergy in information processing, measured at both local and global levels, therefore mediates the effects of structure and can override them entirely, implicating it as a fundamental determinant of group performance. By introducing a causal framework for information processing in collectives, our study delivers a more definitive explanation of collective problem-solving than those offered by structural analysis alone.
Recommended citation: Garg, K., Moser, C., Dromiack, H., Anwarzai, Z., & Ramos-Fernandez, G. (2025). The causal role of synergy in collective problem-solving. https://osf.io/6r2h5_v2