diff --git a/examples/BasicBandit.jsx b/examples/BasicBandit.jsx index b862d16..e699a11 100644 --- a/examples/BasicBandit.jsx +++ b/examples/BasicBandit.jsx @@ -59,7 +59,11 @@ function BasicFruitBandit() {
Keep eating apples, and rejecting the other options, and see how - quickly the bandit learns your preference: + quickly the bandit learns your preference.{" "} +
++ Then switch to preferring oranges, and see how quick the bandit + adapts.
- The bandit can learn the interaction between the context (sunny or - rainy) and the fruit or treat preferences. -
-- If you switch off the context interaction toggles, the recommendations - will no longer depend on the weather. -
-- If you switch off the actionIdFeatures and contextActionIdInteractions, - the recommendations will no longer depend on the specific actionId - ('apple, 'pear', etc), but the probabilities will be the same for all - fruits and all treats. -
-- If you switch off all toggles, all actionIds get the same score and so - the same probability. -
-- Each time you change a toggle, the bandit gets reinstantiated and - retrained on the existing training data. You can see the newly fitted - coefficients in the JSON serialized bandit. -
++ After each recommendation we get a new random context/weather (sunny or + rainy). +
++ You can also click the button to generate a new random context/weather, + and see how that affects the recommendations. +
+ Then switch on and off the toggles to see how that affects the + recommendations. +