Dynamical systems models for controlling multi-agent swarms have demonstrated advances toward resilient, decentralized navigation algorithms.
This article discusses how to create an interactive virtual training program at the intersection of neuroscience, robotics, and computer science for high school students.
To motivate a brain basis of neural computation, we present a dynamical view of intelligence from which we elaborate concepts of sparsity in network structure, temporal dynamics, and interactive learning.
We assess a number of power distribution systems with respect to metrics of signal structure and identify several correlates to system properties and further demonstrate how these metrics relate to performance of some GSP techniques.
Animals and many-robot groups must solve common problems of navigating complex and uncertain environments.