Colloquium on January 7th, 2008

Hiroki Sayama
Binghamton University, State University of New York, USA

Self-organizing structures and behaviors of heterogeneous self-propelled particle swarm models

Self-propelled particle swarm models are computational
models of many particles that are capable of autonomous acceleration
and local kinetic interaction. Their dynamics have been studied in
physics and theoretical biology communities because of their useful
implications for the understanding of collective behavior of various
autonomous agents, such as bacteria, fish, birds, and pedestrians.
Most of earlier studies focused solely on homogeneous particle swarms,
assuming that the same set of kinetic rules uniformly applies to all
the particles. Here we extend our scope to heterogeneous swarms in
which more than one type of particles can co-exist. Through extensive
computer simulations we studied what kind of patterns/motions could
emerge out of the mixtures of multiple types of particles, and found
that heterogeneous self-propelled particle swarms usually undergo
spontaneous phase separation, often leading to the formation of
multilayer structures. Driven by their own endogenous forces, the
aggregates of particles may additionally show more dynamic macroscopic
behaviors, including oscillation, rotation, and linear or even chaotic
motion. Evolutionary exploration further revealed the possibility of
more complex, even biological-looking structures and behaviors when
several different types are blended. These results suggest a novel
direction of understanding and engineering collective behavior of
physical agents such as distributed robotic systems.