Mountain View, CA, United States of America

Tyler Lu

This inventor holds 1 USPTO granted patent. Top assignee: Google Inc.. Active years: 2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Tyler Lu. Retrieved from https://idiyas.com/inventor/tyler-lu

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Innovations of Tyler Lu in Robotic Learning

Introduction

Tyler Lu is an innovative inventor based in Mountain View, CA, who has made significant contributions to the field of robotic learning. His work focuses on addressing challenges in deep Q-learning, particularly the issue of delusional bias in function approximation.

Latest Patents

Tyler Lu holds a patent titled "Mitigating delusional bias in deep Q-learning for robotic and/or other agents." This patent addresses the phenomenon of delusional bias that can occur in function approximation Q-learning. The disclosed techniques involve training and utilizing a value network to mitigate this bias, which can be applied to generate actions for various agents, including robotic and software agents. The patent also explores methods such as a soft-consistency penalty and a search framework over multiple Q-functions to effectively reduce delusional bias.

Career Highlights

Tyler Lu is currently employed at Google Inc., where he continues to develop innovative solutions in the realm of artificial intelligence and robotics. His expertise in deep learning and robotic agents positions him as a valuable asset in the tech industry.

Collaborations

Tyler collaborates with notable colleagues, including Boon Teik Ooi and Craig Edgar Boutilier, who contribute to his research and development efforts in the field.

Conclusion

Tyler Lu's work in mitigating delusional bias in deep Q-learning represents a significant advancement in robotic learning. His contributions not only enhance the functionality of robotic agents but also pave the way for future innovations in artificial intelligence.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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