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SUMMARY:Co-Adaptive Brain Machine Interfaces
DTSTART:20090406T160000
DTSTAMP:20260407T195409Z
UID:46528d6a0f2c9dd3b9f79caf801db83e2ac9ba73da04a8a57dffa117
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Jose C. Principe\, University of Florida\nWe propose a n
 ew co-adaptive close loop paradigm for BMIs based on reinforcement learnin
 g. The subject’s motor cortical neural activity is translated into a val
 ue function for a computer agent (CA) running Q learning that controls the
  actions of a robot to deliver a water reward to the subject. Preliminary 
 results show that the subject and the agent are able to cooperate and impr
 ove their joint performance across task difficulty. 
LOCATION:MXF 1 https://plan.epfl.ch/?room==MXF%201
STATUS:CONFIRMED
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