Todd Andrew Hester

Title: Todd Andrew Hester: Innovator in Neural Network Systems

Introduction

Todd Andrew Hester is a prominent inventor based in Seattle, WA (US). He has made significant contributions to the field of artificial intelligence, particularly in the development of neural network systems. With a total of 2 patents to his name, Hester is recognized for his innovative approaches to machine learning and reinforcement learning.

Latest Patents

Hester's latest patents focus on "Training action selection neural networks using apprenticeship." This invention describes an off-policy reinforcement learning actor-critic neural network system. The system is designed to select actions from a continuous action space for an agent interacting with an environment to perform a task. It utilizes observations that define environment state data and reward data. The architecture includes an actor neural network that learns a policy function mapping state data to action data, while a critic neural network learns an action-value (Q) function. Additionally, a replay buffer is employed to store tuples of state data, action data, reward data, and new state data. This replay buffer also contains demonstration transition data, which comprises tuples from a demonstration of the task within the environment. The system is configured to train both the actor and critic neural networks off-policy using stored tuples from the replay buffer.

Career Highlights

Hester is currently associated with DeepMind Technologies Limited, where he continues to push the boundaries of artificial intelligence research. His work has garnered attention for its potential applications in various fields, including robotics and automated decision-making systems.

Collaborations

Some of Hester's notable coworkers include Olivier Claude Pietquin and Martin Riedmiller. Their collaborative efforts contribute to advancing the understanding and capabilities of neural networks in real-world applications.

Conclusion

Todd Andrew Hester is a key figure in the realm of neural network innovations, with a focus on reinforcement learning systems. His contributions are shaping the future of artificial intelligence and its applications across various industries.