Faculty Contact: Francesco Bullo
Concepts: Distributed dynamical systems, computational algorithms, phase transitions
Datasets: IEEE Power Network Test Systems, Epinions network
Abstract: A broad range of emerging phenomena can be observed in distributed dynamical systems. This training module will lead trainees to experiment and learn by direct observation several emerging dynamical phenomena in different disciplines. The main task is the computer simulation of the following distributed algorithms and dynamical systems: (i) parameter estimation and event detection algorithms in wireless sensor networks, (ii) flocking, aggregation, dispersion and formation control algorithms for large groups of robots and/or simulated animals, (iii) synchronization and phase transition phenomena in coupled oscillators and power networks, (iv) low-complexity distributed algorithms for large-scale optimization, and (v) “rules of thumb” and simplified Bayesian rules for opinion dynamics and network formation.
- Winter 2016: Shadi Mohagheghi and Alex Jones