Cooperative Target Realization in Multi-Agent Systems Allowing Choice-Based Actions

TL;DR

This paper develops optimal control algorithms for multi-agent systems where agents' initial choices influence the target objectives, minimizing control costs while achieving specified targets.

Contribution

It introduces a novel optimal control design methodology for linear multi-agent systems with choice-dependent targets, extending to arbitrary target matrices.

Findings

Derived control algorithms for specific target structures

Compared state-feedback and open-loop strategies

Achieved minimal control cost solutions

Abstract

In this paper, we study cooperative multi-agent systems in which the target objective and the controls exercised by the agents are dependent on the choices they made at initial system time. Such systems have been investigated in several recently published papers, mainly from the perspective of system analysis on issues such as control communication complexity, control energy cost and the feasibility of realization of target functions. This paper continues this line of research by developing optimal control design methodology for linear systems that are collaboratively manipulated by multiple agents based on their distributed choices. For target matrices that satisfy particular structural constraints, we derive control algorithms that can achieve the specified targets with minimum control cost. We compare state-feedback as well as open-loop control strategies for target realization and extend the optimality result to an arbitrary target matrix. The optimal control solutions are obtained by minimizing the average control cost subject to the set of specified target-state constraints by means of modern variation theory and the Lagrange multiplier method.