Re:New Draft of “Reinforcement Learning: An Introduction, Se...
by piedradura on Saturday September 24, 2016 @08:33AM
(#12570690)
What I suggest is to use the function:
if v(s')==1 then 1 else the usual rule.
Re:New Draft of “Reinforcement Learning: An Introduction, Se...
by Eridrus on Saturday September 24, 2016 @11:34AM
(#12571302)
Lets pretend alpha = 1 on a win and alpha = 0.1 on a loss.
Imagine a scenario where you play a game and the opponent plays poorly and you win; you then try and repeat the same thing again, this time the opponent has learnt from their mistakes and beats you. You'll keep playing the same losing move significantly more times because it worked that one time.
I don't know why everyone wants to second-guess the first chapter of the standard textbook in this space with what seems like no experience even thinking about this topic...
Re:New Draft of “Reinforcement Learning: An Introduction, Se...
by piedradura on Saturday September 24, 2016 @11:46AM
(#12571357)
When you lose the value of v' change and so change the value of v.
The scenario you describe is if alhpa=1, and it would do poorly. Try thinking about games where the opponent doesn't play an optimal game. Try thinking of stochastic environments.