Learning Abstract Rules for Swarm Systems

Rule abstraction is an intuitive new tool that we propose for implementing swarm systems. The methods presented in this paper encourage a new paradigm for designing swarm applications: engineers can interact with a swarm at the abstract (swarm) level instead of the individual (agent) level. This is made possible by modeling and learning how particular swarm-level properties arise from low-level agent behaviors. In this paper, we present a procedure for building abstract rules and discuss how they can be used. We also provide experimental results showing that abstract rules can be learned by observation.