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Human Comlex Behavior

A new area of research — fittingly called “complexity science” — embraces the notion that an ant colony and the human brain, the stock market and Facebook all have something in common. All are complex systems, basically huge networks made up of individual components whose behavior is difficult to predict.


Hiroki Sayama

A deeper understanding of these systems' role in nature - and the emergence of computer science tools sophisticated enough to analyze them - offers scientists a more realistic framework for solving today's most vexing problems, from global warming to ethnic conflict.

"The rise of complexity science is not driven by researchers, but actually from the complexity in people's lives," said Hiroki Sayama, an assistant professor in the Department of Bioengineering at Binghamton University. "Ten years ago, a network didn't make much sense."

Today networks and complex systems are everywhere, and there are several university-based centers and journals devoted exclusively to their study.

"It's a fundamental conceptual shift," Sayama said.

It's a different world
At Binghamton, an interdisciplinary group founded in 2007 to study the collective dynamics of complex systems goes by the name CoCo. Perhaps the most striking characteristic of the group is that instead of talking about an interdisciplinary approach, it lives and breathes it.

"There are many people who claim to be interdisciplinary - it's the computer scientist working with the electrical engineers," Sayama, CoCo's director, said with a laugh.

Of course there are plenty of computer science- and engineer-types in CoCo, but they work alongside faculty such as Shelley Dionne, an associate professor in Binghamton's School of Management. She's an MBA-PhD who got her first taste of management not as a budding Wall Streeter, but during a dietetic management rotation toward a degree in nutrition.

"Each one of us is a unique mix," she said.

She was eager to join the group, but quickly discovered that when they finally got face to face, all that interdisciplinary joie de vivre didn't come baggage-free.

"We had no idea how to talk to each other," Dionne said.

In other words, they had swarm intelligence while she had SWOT, that classic business tool of identifying strengths, weaknesses, opportunities and threats.

Other members came to the table with similar diversity: Research interests include public administration, biomimetics and environmental toxicology.

It took time, Dionne said. And, it turned out, a lot of office supplies. "Week after week, drawing pictures on white boards until we were out of ink," she said.

What emerged was a shared passion for understanding group dynamics. The computer scientists might be happily creating swarm simulators or explaining the latest in agent-based modeling, but, she too, could dive headfirst into creating ways for businesses to survive the shift from Dilbert days to dynamic global leadership.

"Gone are the days I sit in my cubicle alone for eight hours a day," she said, describing today's corporate environment. "Gone."

It is exactly that rapid-fire change of today's business climate that has shown the pressing need for a new framework, said Ken Thompson, a United Kingdombased expert in the area of bioteaming, swarming and virtual enterprise networks and teams, which draws heavily on the understanding of complex systems in nature. His most recent book is Bioteams: High Performance Teams Based on Nature's Most Successful Designs.

Traditional business teams rely too heavily on a single dominant structure - command and control, also known as individually led teams, he said, drawing from the military. Such an approach "served us well in the era of mass production when costs, consistency and compliance were everything," Thompson said.

But that model falls well short in today's world full of "networks, dynamic alliances, virtual collaborations - where agility, innovation, added-value and responsiveness are king," he said. "We urgently need to find a new model which recognizes that organizations are not predictable systems, like clocks, but unpredictable ecosystems, like living things. The natural place to look for this model is nature itself with its numerous examples of self-organizing systems and teams in ants, bees, dolphins, wolves, geese and many more."

One of Sayama's research goals is to create some way to self-organize heterogeneous swarms with several distinct types of particles into specific spacial patterns so one can evolve the internal mechanism. He envisions a system in which, collectively, robots can spontaneously create behaviors.

 

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