Social contribution in the design of adaptive machines on the web
Proceedings of the 15th International Conference on the Synthesis and Simulation of Living Systems (ALife 2016), , , 2016
Abstract: The Web has created new opportunities for interactive problem
solving and design by large groups. In the context of
robotics, we have shown recently that a crowd of non-experts
are capable of designing adaptive machines over the Web.
However, determining the degree to which collective contribution
plays a part in these tasks requires further investigation.
We hypothesize that there exist subtle yet measurable
social dynamics that occur during the collaborative design of
robots on the Web. To test this, we enabled a crowd to rapidly
design and train simulated, web-embedded robots1
. We compared
the robots designed by a socially-interacting group of
individuals to another group whose members were isolated
from one another. We found that there exists a latent quality
in the robots designed by the social group that was significantly
less prevalent in the robots designed by individuals
working alone. Thus, there must exist synergies in the former
group that facilitate this design task. We also show that this
latent quantity correlates with the desired design outcome,
which was fast forward locomotion. However, the quantity –
when distilled into its component parts – is not more prevalent
in one group than another. This finding demonstrates that
there are indeed traces left behind in the machines designed
by the crowd that betray the social dynamics that gave rise to
them. Demonstrating the existence of such quantities and the
methodology for extracting them presents opportunities for
crafting interfaces to magnify these synergies and thus improve
collective design of robots over the web in particular,
and crowd design activities in general.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).