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Ph.D. Proposal Oral Exam - Zixuan Wu

Title:  Model-assisted Reinforcement and Imitation Learning in Adversarial-Collaborative Robotic Systems

Committee: 

Dr. Gombolay, Advisor  

Dr. Vela, Chair

Dr. Ravichandar

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Summary

The objective of the proposed research is to show constructing agent behavior or intention models can enable reinforcement learning (RL) training in partially observable environments and help IL knowledge transferring from expert domain to real-world robotic systems. My approaches will be validated in pursuit-evasion games, adversarial communications, and real-world wheelchair tennis robot systems.

Details

Thursday
Mar 20 2025
12:00pm - 02:00pm

Location: Room 053, CoC

In campus calendar: No

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  • Workflow status: Published
  • Created by: Daniela Staiculescu
  • Created: 03/17/2025
  • Modified By: Daniela Staiculescu
  • Modified: 03/17/2025

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