Implemented thompson sampling in R

Author: tanvirrazin

part_6-re-inforcement-learning/thompson_sampling/thompson_sampling.R

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+# Importing the dataset
+dataset = read.csv('../../data_files/Ads_CTR_Optimisation.csv')
+
+# Implementing Thompson Sampling
+N = 10000
+d = 10
+ads_selected = integer()
+numbers_of_rewards_1 = integer(d)
+numbers_of_rewards_0 = integer(d)
+total_reward = 0
+
+for (n in 1:N) {
+    ad = 0
+    max_random = 0
+
+    for (i in 1:d) {
+        random_beta = rbeta(
+            n=1,
+            shape1=numbers_of_rewards_1[i]+1,
+            shape2=numbers_of_rewards_0[i]+1
+        )
+
+        if (random_beta > max_random) {
+            max_random = random_beta
+            ad = i
+        }
+    }
+
+    ads_selected = append(ads_selected, ad)
+    reward = dataset[n, ad]
+
+    if (reward == 1) {
+        numbers_of_rewards_1[ad] = numbers_of_rewards_1[ad] + 1
+    } else if (reward == 0) {
+        numbers_of_rewards_0[ad] = numbers_of_rewards_0[ad] + 1
+    }
+
+    total_reward = total_reward + reward
+}
+
+# Visualising the results - Histogram
+hist(ads_selected,
+     col = 'blue',
+     main = 'Histogram of ads selections',
+     xlab = 'Ads',
+     ylab = 'Number of times each ad was selected')