The human brain is wondrous in its capabilities. The rules that govern its prowess at so many tasks are becoming slightly clearer everyday. In this video, I'll highlight how 4 key reinforcement learning algorithms help explain how the human brain works, specifically through the lens of the neurotransmitter known as 'dopamine'. These algorithms have been used to help train everything from autopilot systems for airplanes, to video game bots. TD-Learning, Rescorla-Wagner, Kalman Filters, and Bayesian Learning, all in one go!
Code for this video:
https://github.com/llSourcell/Mathematics_of_Dopamine
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This video is apart of move 37.
Github Syllabus:
https://github.com/llSourcell/Move_37_Syllabus
More learning resources:
https://www.youtube.com/watch?v=pYyUSh1veoo
https://www.youtube.com/watch?v=LyCpuLikLyQ
https://www.youtube.com/watch?v=CaCcOwJPytQ
https://www.youtube.com/watch?v=C2OUfJW5UNM
https://dash.harvard.edu/bitstream/handle/1/23845336/4633133.pdf?sequence=1&isAllowed=y
https://web.stanford.edu/group/pdplab/pdphandbook/handbookch10.html
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