Noise-Induced Adaptive Decision-Making in Ant-Foraging

Ant foraging is a paradigmatic example of self-organized behavior. We give new experimental evidence for previously unobserved short-term adaptiveness in ant foraging and show that current mathematical foraging models cannot predict this behavior. As a true extension, we develop Itô diffusion models that explain the newly discovered behavior qualitatively and quantitatively. The theoretical analysis is supported by individual-based simulations. Our work shows that randomness is a key factor in allowing self-organizing systems to be adaptive. Implications for technical applications of Swarm Intelligence are discussed.