Guiding Self-Organization in Systems of Cooperative Mobile Agents - Advancing Artificial Intelligence Through Biological Process Applications - page 269

Chapter XV
Guiding Self-Organization
in Systems of Cooperative
Mobile Agents
Alejandro Rodríguez
University of Maryland, USA
Alexander Grushin
University of Maryland, USA
James A. Reggia
University of Maryland, USA
AbSTRACT
Drawing inspiration from social interactions in nature, swarm intelligence has presented a promising
approach to the design of complex systems consisting of numerous, simple parts, to solve a wide variety
of problems. Swarm intelligence systems involve highly parallel computations across space, based heavily
on the emergence of global behavior through local interactions of components. This has a disadvantage
as the desired behavior of a system becomes hard to predict or design. Here we describe how to provide
greater control over swarm intelligence systems, and potentially more useful goal-oriented behavior,
by introducing hierarchical controllers in the components. This allows each particle-like controller to
extend its reactive behavior in a more goal-oriented style, while keeping the locality of the interactions.
We present three systems designed using this approach: a competitive foraging system, a system for the
collective transport and distribution of goods, and a self-assembly system capable of creating complex
3D structures. Our results show that it is possible to guide the self-organization process at different levels
of the designated task, suggesting that self-organizing behavior may be extensible to support problem
solving in various contexts.