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The problem of controlling multi-agent systems under different models of information sharing among agents has received significant attention in the recent literature. In this paper, we consider a setup where rather than committing to a fixed information sharing protocol (e.g. periodic sharing or no sharing etc), agents can dynamically decide at each time step whether to share information with each other and incur the resulting communication cost. This setup requires a joint design of agents communication and control strategies in order to optimize the trade-off between communication costs and control objective. We first show that agents can ignore a big part of their private information without compromising the system performance. We then provide a common information approach based solution for the strategy optimization problem. This approach relies on constructing a fictitious POMDP whose solution (obtained via a dynamic program) characterizes the optimal strategies for the agents. We also show that our solution can be easily modified to incorporate constraints on when and how frequently agents can communicate.
We consider the optimal coverage problem where a multi-agent network is deployed in an environment with obstacles to maximize a joint event detection probability. The objective function of this problem is non-convex and no global optimum is guarantee
This paper studies an optimal consensus problem for a group of heterogeneous high-order agents with unknown control directions. Compared with existing consensus results, the consensus point is further required to an optimal solution to some distribut
We propose a neural network approach for solving high-dimensional optimal control problems. In particular, we focus on multi-agent control problems with obstacle and collision avoidance. These problems immediately become high-dimensional, even for mo
Distributed algorithms for both discrete-time and continuous-time linearly solvable optimal control (LSOC) problems of networked multi-agent systems (MASs) are investigated in this paper. A distributed framework is proposed to partition the optimal c
Platooning has been exploited as a method for vehicles to minimize energy consumption. In this article, we present a constraint-driven optimal control framework that yields emergent platooning behavior for connected and automated vehicles operating i