We introduce AutoMoDe: a novel approach to the automatic design of control software for robot swarms. The motivation behind the design approach adopted in AutoMoDe recalls the approach commonly adopted in machine learning for dealing with the bias-variance tradedoff: to obtain suitably general solutions with low variance, an appropriate design bias is injected. AutoMoDe produces robot control software by selecting, instantiating, and combining preexisting parametric modules that represent atomic behaviors---the introduced bias. The resulting control software is a probabilistic finite state machine in which each node is an atomic behavior. The topology, the transition rules and the values of the parameters are obtained automatically via an optimization process that maximizes a task-dependent objective function.
swarm robotics, automatic design