Continuous Evolutionary Computation

Description:
Continuous evolutionary computation makes use of cyclic genetic algorithms (CGAs) and analog VLSI field computers to solve problems using adaptive continuous computations. CGAs are being applied to produce fault-tolerant gaits for the hexapod robot Stiquito by evolving gait cycles that can be generated by an artificial neural field network. Continuous evolutionary computation strives to mesh genetic algorithms and field computing to design dynamical systems that adapt to their environment. A long-term application of CGAs is the design of an adaptive controller for the Indiana University Cyclotron.

Graduate Student Researcher: Gary A. Parker.

Faculty Advisors: Jonathan W. Mills, Gregory A. Rawlins.

Support:

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Modern Analog Field Computing | Related Projects | Analog VLSI and Robotics Laboratory
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