Fifty participants from SFI’s various education programs tested their new knowledge on a tangible, real-world problem during the Institute's first Complexity Challenge.
In August of this year, SFI External Professor John Miller and SFI's education office introduced Complexity Challenges as a way to let participants in SFI's educational programs — including our online Complexity Explorer platform, Complex Systems Summer School, Short Courses, and Research Experience for Undergraduates — apply their studies.
For the inaugural challenge, which ran August 16 through September 30, SFI teamed up with the MITRE Corporation and its longtime SFI ACtioN representative Matt Koehler. Fifty participants from SFI’s alumni and Complexity Explorer communities signed up to participate.
The problem had to do with decentralized delivery — think warehouse organization, package delivery, airline routing, or self-driving ride services. In this case, the problem was abstracted as a giant checkerboard with the challenge of getting checkers from varying starting and ending points using only simple rules and local information.
“We don’t have some ‘right answer’ in mind,” Miller said. “What we care about is good solid scientific thinking that uses the various tools and ideas from complex systems science to derive novel solutions.”
The winning two solutions were submitted by Mika J. Straka, a Ph.D. student in complex systems in Lucca, Italy, and Ellen Badgley, a software engineer at the MITRE Corporation. Honorable Mentions were from Zhiya Zuo, a University of Iowa Ph.D. candidate in information science, and Rohan Mehta, a graduate student in mathematical biology at Stanford. (Read more about the top two solutions and two honorable mentions on SFI's Complexity Explorer.)
The top four solutions each took unique approaches to the Challenge. Mehta says his background in mathematical biology likely influenced his decision to consider organic autonomous things like people and animals as they move through a common space. Zuo initially drew on literature regarding pedestrian dynamics before building an agent-based model. Straka started with an assumption that the challenge referred to autonomous vehicles, but also considered surface growth dynamics to create a solution. Badgley also imagined an autonomous vehicle scenario and used agent-based modeling to create a solution using "extremely simple measures of efficiency." Badgley's solution was ranked first in peer and mentor selection and Miller's ranking placed hers and Straka's solution as the top two.
Though she is employed by the partner institution, Badgley says she had no idea who was behind the Challenge initially and completed the challenge outside of work. "I decided to take part in the challenge with absolutely no thought of "winning," but primarily to give myself an excuse to dive into an interesting complexity problem, explore some new tools and techniques, and help SFI refine this program further," says Badgley, who was a 2016 Complex Systems Summer School student. Badgley declined any award due to her employment at MITRE.
Straka, also a 2016 CSSS student, enjoyed melding his background in theoretical physics with other disciplines during this Challenge. "It gave me the perfect occasion to relive the Santa Fe approach: take a problem, and play with it. Look at it from different angles, consider different approaches, search for parallels to other systems. And above all: have fun," he says.
Complexity Challenges bring benefits to all involved, says Gabby Beans, SFI’s Program Manager for Online Education. “For the ACtioN members, we’re hoping they get some creative solutions,” she says. “For the students, along with the unique learning opportunity, we’re also hoping to showcase their talents to potential employers.”
In the future, Complexity Challenges may form the basis of capstone projects for online certificate or degree programs offered by SFI, she says.
“At the end of the day, it doesn’t matter how much book-learning you have or how many problem-sets you solve,” says Miller. “Creative, interdisciplinary complex systems thinking is best tested when applied to the real world.”
Watch the video, "The Inaugural Complexity Challenge: Inspiration and Results." (13:11)