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Communicative Capital for Prosthetic Agents
This work presents an overarching perspective on the role that machine intelligence can play in enhancing human abilities, especially those that have been diminished due to injury or illness.
Using Learned Predictions as Feedback to Improve Control and Communication with an Artificial Limb: Preliminary Findings
Our study therefore contributes initial evidence that prediction learning and machine intelligence can benefit not just control, but also feedback from an artificial limb.
Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb
In the present work, we explore the use of temporal-difference learning and GVFs to predict when users will switch their control influence between the different motor functions of a robot arm.
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