We consider the distributed optimization problem for a multi-agent system. Here, multiple
agents cooperatively optimize an objective by sharing information through a communication …

Human-swarm interaction is facilitated by a low-dimensional encoding of the swarm
formation, independent of the (possibly large) number of robots. We propose using image …

We describe SH-SVL, a parameterized family of first-order distributed optimization
algorithms that enable a network of agents to collaboratively calculate a decision variable …

Distributed convex optimization algorithms employ a variety of methods for achieving exact
convergence to the global optimal value (modulo numerical precision): some use time …

The field of distributed optimization algorithms is wide and growing, and new techniques for
categorizing and analyzing existing algorithms are continually being developed. In this …

In distributed problems where consensus between agents is required but average
consensus is not desired, it can be necessary for each agent to know not only the data of …

Multi-agent systems have been largely used over decades to model and study groups of
interconnected independent entities acting together, most often collaboratively, towards …