Explore deep reinforcement learning techniques for object tracking in this 30-minute lecture from the University of Central Florida. Learn about different types of learning, deep learning fundamentals, and reinforcement learning principles. Discover the concept of value functions as predictions of future rewards and various approaches to reinforcement learning. Delve into action-driven object tracking, including problem definition in an RL setting, action-decision networks, and training methods such as supervised learning, reinforcement learning, and online adaptation. Gain insights into self-comparison techniques and their applications in object tracking systems.