In many existing multi-agent reinforcement learning tasks, each agent observes all the other agents from its own perspective. addition, training process is centralized, namely critic of can access policies agents. This scheme has certain limitations since every single only obtain information neighbor due to communication range in practical applications. Therefore, this paper, a distributed deep...

Various efforts have been devoted to developing stabilizing distributed model predictive control (MPC) schemes for tracking piecewise constant references. In these schemes, terminal sets are usually computed offline and used in the MPC online phase guarantee recursive feasibility asymptotic stability. Maximal invariant do not necessarily respect structure of network, hindering implementation co...

This paper presents a distributed model reference adaptive control scheme for optimal tracking of an interconnected dynamical system in the presence system/interconnection uncertainties. A selection which achieves nominal is introduced by using linear quadratic regulator theory. Then law developed uncertain system, where it employs specified model. It shown that desired behaviour such output as...