Adversarial and Cooperation Tasks in Multi- Agent System with Large Language Models

The integration of large language models (LLMs) and multi-agent systems (MAS) within multi-unmanned aerial vehicle (multi-UAV) systems offers unprecedented capabilities for both adversarial and cooperative missions. This paper explores the synergistic use of LLMs and MAS to enhance decision-making, coordination, and adaptability in complex and dynamic combat scenarios. We propose a framework that leverages the strengths of LLMs for strategic planning and MAS for real-time tactical execution. Through simulations and theoretical analysis, we demonstrate the potential benefits and challenges of such an integrated approach.