1SD51 Network dynamics and information

Information Theoretic MPC Using Neural Network Dynamics

We introduce an information theoretic model predictive control (MPC) algorithm that is capable of controlling systems with dynamics represented by multi-layer neural networks and subject to complex cost criteria. The proposed approach is validated in two difficult simulation scenarios, a cart-pole swing up and quadrotor navigation task, and on real hardware on a 1/5th scale vehicle in an aggres...

Universality in network dynamics Supplementary Information

Global Information Sharing under Network Dynamics

We study how to spread k tokens of information to every node on an n-node dynamic network, the edges of which are changing at each round. This basic gossip problem can be completed in O(n + k) rounds in any static network, and determining its complexity in dynamic networks is central to understanding the algorithmic limits and capabilities of various dynamic network models. Our focus is on toke...

Network Characteristics and Dynamics: Reciprocity, Competition and Information Dissemination

NETWORK CHARACTERISTICS AND DYNAMICS: RECIPROCITY, COMPETITION AND INFORMATION DISSEMINATION Report Title Networks are commonly used to study complex systems. This often requires a good understanding of the structural characteristics and evolution dynamics of networks, and also their impacts on a variety of dynamic processes taking place on top of them. In this thesis, we study various aspects ...

Co-evolutionary Dynamics of Information Diffusion and Network Structure

Information diffusion in online social networks is obviously affected by the underlying network topology, but it also has the power to change that topology. Online users are constantly creating new links when exposed to new information sources, and in turn these links are alternating the route of information spread. However, these two highly intertwined stochastic processes, information diffusi...