Distributed Actor-Critic Algorithms for Multiagent Reinforcement Learning Over Directed Graphs

Actor-critic (AC) cooperative multiagent reinforcement learning (MARL) over directed graphs is studied in this article. The goal of the agents in MARL is to maximize the globally averaged return in a distributed way, i.e., each agent can only exchange information with its neighboring agents. AC methods proposed in the literature require the...

Distributed Adaptive Resource Allocation: An Uncertain Saddle-Point Dynamics Viewpoint

This paper addresses distributed adaptive optimal resource allocation problems over weight-balanced digraphs. By leveraging state-of-the-art adaptive coupling designs for multiagent systems, two adaptive algorithms are proposed, namely a directed-spanning-tree-based algorithm and a node-based algorithm. The benefits of these algorithms are...

Impact of Network Topology on the Resilience of Vehicle Platoons

This paper presents a comprehensive study on the impact of information flow topologies on the resilience of distributed algorithms that are widely used for estimation and control in vehicle platoons. In the state of the art, the influence of information flow topology on both internal and string stability of vehicle platoons has been well...

Distributed Adaptive Optimization with Weight-Balancing

This article addresses the continuous-time distributed optimization of a strictly convex summation-separable cost function with possibly nonconvex local functions over strongly connected digraphs. Distributed optimization methods in the literature require convexity of local functions, or balanced weights, or vanishing step sizes, or algebraic...

A Directed Spanning Tree Adaptive Control Solution to Time-Varying Formations

In this article, the time-varying formation and time-varying formation tracking problems are solved for linear multiagent systems over digraphs without the knowledge of the eigenvalues of the Laplacian matrix associated with the digraph. The solution to these problems relies on an approach that generalizes the directed spanning tree (DST)...

Consensus in high-power multiagent systems with mixed unknown control directions via hybrid Nussbaum-based control

This work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed...