Using a collection of humans as an execution testbed for swarm algorithms

摘要

To gain insight into swarm algorithms, researchers can study insect societies and other natural collectives, program multi-agent software simulations or build groups of cooperating robots. In our research, we consider another resource: swarms of humans. Human swarms provide three primary benefits: quick feedback and evaluation of swarm algorithms, experience with high-level swarm directives instead of low-level agent programs, and a source of swarm algorithms that can potentially be reverse-engineered for use in other applications. Planning is a human's preferred problem solving methodology because we are intelligent creatures with high-level communication skills. Due to the intelligence of the agents, human swarms can be quickly programmed, for subsequent observation and analysis. This paper describes human swarm experiments designed for gathering information on swarm algorithms. At these events 100 volunteers, wearing data-encoded T-shirts, work together to perform tasks of differing degrees of complexity. Researchers provide simple instructions for each task (programming the swarm), record the swarm's behavior (videotaped observation) and analyze the results (problem identification and algorithm-mining). We demonstrate the viability of this research by presenting the quick identification of a swarm algorithm "bug" and by producing a software implementation of a swarm algorithm gleaned from our observations.