Coalition Control Model: A Dynamic Resource Distribution Method Based on Model Predicative Control

TL;DR

This paper introduces a Coalition Control Model based on Model Predictive Control to dynamically optimize resource distribution among fishing fleets, improving efficiency in complex scenarios.

Contribution

It presents a novel coalition control approach integrating communication, coalition formation, and Nash bargaining for resource distribution.

Findings

Successfully distributed resources in a simulated fishing model

Demonstrated dynamic coalition formation and stabilization

Achieved equilibrium states through Nash bargaining

Abstract

Optimization of resource distribution has been a challenging topic in current society. To explore this topic, we develop a Coalition Control Model(CCM) based on the Model Predictive Control(MPC) and test it using a fishing model with linear parameters. The fishing model focuses on the problem of distributing fishing fleets in certain regions to maximize fish caught using either exhaustive or heuristic search. Our method introduces a communication mechanism to allow fishing fleets to merge or split, after which new coalitions can be automatically formed. Having the coalition structure stabilized, the system reaches the equilibrium state through the Nash-Bargaining process. Our experiments on the hypothetical fishing model demonstrated that the CCM can dynamically distribute limited resources in complex scenarios.