BanditsBook | Code for my book on Multi-Armed Bandit Algorithms | Learning library
kandi X-RAY | BanditsBook Summary
kandi X-RAY | BanditsBook Summary
Code for my book on Multi-Armed Bandit Algorithms
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QUESTION
This is a second attempt at correcting my earlier version that lives here. I am translating the epsilon-greedy algorithm for multiarmed bandits.
A summary of the code is as follows. Basically, we have a set of arms, each of which pays out a reward with a pre-defined probability and our job is to show that by drawing at random from the arms while drawing the arm with the best reward intermittently eventually allows us to converge on to the best arm.
The original algorithm can be found here.
...ANSWER
Answered 2018-Apr-09 at 10:32In this piece of code:
QUESTION
I am translating the epsilon-greedy algorithm for multiarmed bandits from here. This is a rather nice demonstration of the power and elegance of Rcpp. However, the results from this version do not tally with the one that is mentioned in the link above. I am aware that this is probably a very niche question but have no other venue to post this on!
A summary of the code is as follows. Basically, we have a set of arms, each of which pays out a reward with a pre-defined probability and our job is to show that by drawing at random from the arms while drawing the arm with the best reward intermittently eventually allows us to converge on to the best arm. A nice explanation of this algorithm is provided by John Myles White.
Now, to the code:
...ANSWER
Answered 2018-Apr-03 at 12:18I don't know how the bandits are supposed to work, but a little standard debugging (ie: look at the values generated) revealed that you generated lots of zeros.
After fixing some elementary errors (make your C/C++ loops for (i=0; i ie start at zero and compare with less-than) we are left with other less subtle errors such as
runif(1,N)
cast to int
not giving you a equal range over N values (hint: add 0.5 and round and cast, or sample one integer from the set of 1..N integers).
But the main culprit seems to be your first argument epsilon. Simply setting that to 0.9 gets me a chart like the following where you still the issue with the last 'half' unit missing.
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