Collective Animal Behavior

Firefly flashing and human applause share the same mathematical model. So do ants foraging for food and cockroaches finding shelter. This is the central revelation of Sumpter's synthesis: simple repeated interactions between individuals—none of them 'smart'—produce complex adaptive patterns at the group level.

The book bridges behavioral ecology with self-organization theory from physics and mathematics. For each phenomenon—movement, information transfer, decision-making, synchronization, structure-building—Sumpter shows that the same equations explain behavior across species. A model that predicts how ants suddenly switch from scattered exploration to organized trail-following also predicts the critical threshold where applause becomes synchronized.

Here's the counterintuitive business insight: you don't need smart parts to build a smart whole. Termite mounds, ant networks, and human crowds emerge from repeated interactions between agents following simple local rules. The intelligence is in the interaction pattern, not the individual components. When you see sophisticated organizational behavior, look for the simple rules generating it—and when you want to design collective behavior, start with interaction rules, not individual training.

Sumpter mathematically demonstrates what Seeley found experimentally with honeybees: decentralized systems following simple rules consistently outperform centralized control. The book is the quantitative foundation for understanding why swarm intelligence works—and crucially, where it fails. Simple rules work until the environment changes faster than the rules can adapt.