The Evolution of AI in Command and Control

The development of natural language processing (NLP) technologies has significantly evolved, particularly in relation to command and control applications. Early work on multi-agent systems laid the foundation for understanding how AI could effectively operate within controlled environments by breaking down complex tasks into manageable components. This historical context highlights the transition from limited AI capabilities to today's advanced large language models that can handle multiple roles simultaneously. The current paradigm emphasizes defining specific responsibilities for agents to optimize their performance in various contexts, reflecting a shift toward more decentralized AI architectures.