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View Code? Open in Web Editor NEWReinforcement learning algorithms
License: MIT License
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GTD algorithm implementation
I was reading the GTD implementation and I got a little confused about updating the weights. Based on the code these are the update rules.
self.w += alpha*(delta*self.e + gm_p*(1-lm_p)*np.dot(self.e, self.h)*xp)
self.h += beta*(delta*self.e + np.dot(self.h, x)*x)
However, based on Maei's thesis the update rules are a little different.
self.w += alpha*(delta*self.e - gm_p*(1-lm_p)*np.dot(self.e, self.h)*xp)
self.h += beta*(delta*self.e - np.dot(self.h, x)*x)
Is there a reason for these differences?
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