Abstract: Evolutionary computation (EC) has been used extensively for the automated design of robot controllers (see  for an overview); more recently, robots themselves have been automatically designed using evolutionary techniques ,: the morphology and controller of the robot is evolved together to produce robots that exhibit increasing efficacy at performing the desired task. Evolutionary techniques are a kind of stochastic search: hundreds or thousands of candidate solutions to a problem are tested (in the case of robotics, a robot controller or the robot itself), and those that solve the given problem better (such as a robot that performs a desired task well) are retained and modified, and those that are inferior are deleted. Because of the need to perform many evaluations, robot simulators are used to evolve controllers, which can then be downloaded on to the physical robot. With the maturation of three-dimensional printing technologies, it has been demonstrated  that not only can robots be automatically designed, but the prospect of automated robot fabrication will become possible in the near future: robot morphologies may be evolved in simulation, and then the entire robot may be automatically printed. We argue that integrated robot design and robot manufacture machines could be of use in planetary exploration for two main reasons: robot groups would not have to be flown from Earth to their target site, thus minimizing payload; and the design and behaviors of robots could be altered on site in response to unforseen environmental factors. This latter point could be achieved by deploying robots into the remote environment, and having them communicate sensor data back to the design/manufacture machine. The machine could then use this data to automatically …
[edit database entry]
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).