Abstract

How is indecision broken? Many biological systems, from honeybees and bird flocks to bacteria, neurons, and humans, face indecision when choosing between options in situations in which the fitness or even the survival of the system are at stake. Intelligent artificial systems face the same conundrums, for instance, an autonomous vehicle deciding whether to avoid a suddenly appeared obstacle on the left or on the right, or an autonomous robot swarm that needs to rapidly allocate itself across different tasks in risk-critical situations, like search and rescue. How can a system react rapidly in face of indecision, particularly in situations it had never encountered before?

Biology teaches us that excitable and multi-stable dynamical systems provide an analog, flexible and, yet, robust solution to make decisions from indecisions. The resulting mathematical models are grounded in feedback and bifurcation theories, and, beyond analysis, they provide powerful tools for the design of artificial bio-inspired indecision-breaking decision-makers.