This presentation introduces Cognitive Electronic Warfare (CogEW) as the next step in the evolution of AI-enabled radiofrequency (RF) systems. CogEW unifies the principles of cognitive radio, cognitive radar, and cognitive electronic warfare (EW). These systems share the same goal: perceiving, deciding, and acting in dynamic and uncertain electromagnetic environments in real time. This presentation will illustrate how AI techniques such as situation assessment, decision-making, and machine learning are applied across RF domains and explain what makes EW uniquely demanding. Unlike many AI applications, EW systems must learn from novel experiences during the mission itself without human supervision, often from a single observation. This requires self-supervised, reinforcement-driven adaptation on operational timescales. Consequently, traditional validation approaches often fall short. The focus must shift from validating static models to validating the learning process itself. This talk will discuss the implications for test infrastructure, including the need for automated, closed-loop, multi-resolution testing, and methods for assessing the effectiveness of learned actions. It draws material from the book Cognitive Electronic Warfare: An Artificial Intelligence Approach, highlighting the promise and practical challenges of deploying cognitive systems.

In this webinar, you will learn how to/learn more about:

• How cognitive systems perceive the environment and take actions to achieve goals.
• How traditional approaches to EW are failing and automated learning improve performance in novel RF environments.
• Machine learning (ML) vs. Cognitive Training
• Information flow in a cognitive system
• Testing for cognitive systems with focus on the process