MORE | Summer 2021

Perspective Variant Preference-Based Learning with Quadcopter Swarms

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Preference-based learning allows for non-expert users to interact with reinforcement learning agents in a way that they can shape their behaviors. This work intends to push the current implementations of preference-based learning forward by introducing binocular vision, multiple perspectives of the agent performing the actions, and multi-agent environments. These three improvements on the existing implementations will allow for preference-based learning to be more robust and useful in portraying an accurate representation of the actions that the user wishes for the agent to perform.

Student researcher

Calvin Shores Ferraro

Engineering (robotics)

Hometown: Dallas, Texas, United States

Graduation date: Fall 2021

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