This paper describes the usefulness of renewable energy throughout the world to generate
power. Renewable energy adds a remarkable scope in power system. Renewable energy …

Recently, deep reinforcement learning (RL) methods have been applied successfully to
multi-agent scenarios. Typically, the observation vector for decentralized decision making is …

We consider a general multi-agent convex optimization problem where the agents are to
collectively minimize a global objective function subject to a global inequality constraint, a …

This self-contained introduction to the distributed control of robotic networks offers a
distinctive blend of computer science and control theory. The book presents a broad set of …

A robust leader–follower formation tracking design using connectivity-maintaining and
collision-avoiding performance functions is developed for multiple uncertain underactuated …

In this review, we present a comprehensive perspective on communication-aware robotics,
an area that considers realistic communication environments and aims to jointly optimize …

We present a method that enables resilient formation control for mobile robot teams in the
presence of noncooperative (defective or malicious) robots. Recent results in network …

We provide a theoretical framework for controlling graph connectivity in mobile robot
networks. We discuss proximity-based communication models composed of disk-based or …

The ability of a robot team to reconfigure itself is useful in many applications: for
metamorphic robots to change shape, for swarm motion towards a goal, for biological …

Control of mobile networks raises fundamental and novel problems in controlling the
structure of the resulting dynamic graphs. In particular, in applications involving mobile …